{"meta":{"query_hash":"20cdafadb87f","filters":{"venue":"Biomedical Engineering Letters"},"cohort_total":24,"direct_labels_cover":0,"predictions_cover":24,"exported":24,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/20cdafadb87f","api":"https://metacan.xera.ac/api/v1/cohort?venue=Biomedical+Engineering+Letters"},"results":[{"id":"W1989310519","doi":"10.1007/s13534-013-0098-7","title":"3D surface reconstruction of stereo endoscopic images for minimally invasive surgery","year":2013,"lang":"en","type":"article","venue":"Biomedical Engineering Letters","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Tech University; University of Toronto","funders":"Hospital for Sick Children","keywords":"Computer vision; Artificial intelligence; Computer science; Imaging phantom; Context (archaeology); Endoscope; 3D reconstruction; Surface reconstruction; Process (computing); Surface (topology); Radiology; Medicine; Mathematics; Geology","score_opus":0.008076347515000111,"score_gpt":0.17876238176956757,"score_spread":0.17068603425456746,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1989310519","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08152689,0.00030351637,0.9114225,0.00020505047,0.00007157234,0.00007185466,0.0005914793,0.0020221856,0.003784971],"genre_scores_gemma":[0.57443863,0.0008430861,0.4194042,0.0000764058,0.000032147786,0.00006571352,0.0011082232,0.00054335134,0.0034882303],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99975914,0.000026099528,0.000009169462,0.00001737284,0.00016933998,0.000018859155],"domain_scores_gemma":[0.99979657,0.00005109071,0.000017808303,0.000053770676,0.00006787385,0.000012986185],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00022667242,0.00048095032,0.00030848302,0.0007376443,0.00012221852,0.00072050595,0.00035759225,0.00056267367,0.004016213],"category_scores_gemma":[0.00072929024,0.00054221676,0.0006074394,0.00058963324,0.00017081479,0.00047033367,0.0004324272,0.0006103503,0.001118165],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00040655557,0.0001699672,0.0027406109,0.00033467714,0.00008699474,0.00033148445,0.00022289158,0.11132874,0.39041397,0.0067590205,0.00772513,0.47948],"study_design_scores_gemma":[0.000023019025,0.000085165164,0.004797417,0.000025032901,0.000023412336,0.0005619926,0.00007007968,0.8888946,0.09830206,0.0017254995,0.0054484583,0.00004318266],"about_ca_topic_score_codex":0.0013834712,"about_ca_topic_score_gemma":0.0017137701,"teacher_disagreement_score":0.004016213,"about_ca_system_score_codex":0.0002011307,"about_ca_system_score_gemma":0.000594608,"threshold_uncertainty_score":0.013435602},"labels":[],"label_agreement":null},{"id":"W2087996395","doi":"10.1007/s13534-011-0034-7","title":"Rheology of osteoarthritic synovial fluid mixed with viscosupplements: A pilot study","year":2011,"lang":"en","type":"article","venue":"Biomedical Engineering Letters","topic":"Osteoarthritis Treatment and Mechanisms","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Vancouver Coastal Health Research Institute; University of British Columbia","keywords":"Synovial fluid; Viscosupplementation; Osteoarthritis; Rheology; Medicine; Synovial joint; Knee Joint; Cartilage; Surgery; Materials science; Pathology; Articular cartilage; Intra articular; Anatomy; Composite material","score_opus":0.018460708916484794,"score_gpt":0.2143626573535883,"score_spread":0.1959019484371035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2087996395","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99855584,0.00042876383,0.0006358381,0.000013668312,0.000016785765,0.000045609515,0.000027684497,0.0000056249564,0.0002702286],"genre_scores_gemma":[0.9978009,0.0004281572,0.0011230264,0.00002825614,0.00003002826,0.00003462784,0.00005122575,0.00000563649,0.00049820263],"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","domain_scores_codex":[0.99960655,0.00012973821,0.000040519844,0.000051621308,0.00009647248,0.000075096454],"domain_scores_gemma":[0.99956006,0.00017558454,0.00008608925,0.00004123373,0.000076279284,0.0000607599],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007506623,0.00047230916,0.00042708352,0.00038868978,0.00038217893,0.00048856426,0.00026254778,0.000388707,0.00166228],"category_scores_gemma":[0.00086589484,0.00014948135,0.00046282323,0.00025867193,0.0004565445,0.00062792434,0.00040332042,0.00045663072,0.00025685455],"study_design_candidate":"observational","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0035467534,0.0010823982,0.0012631296,0.00011321389,0.00002307671,0.00016467326,0.00022065557,0.00015290239,0.9889565,0.000051713905,0.000029588553,0.004395244],"study_design_scores_gemma":[0.0002609898,0.029518062,0.006707991,0.000029700572,0.0001773011,0.00040744265,0.0004117257,0.0013218408,0.95986074,0.00004458763,0.0012325154,0.000027031308],"about_ca_topic_score_codex":0.00037208054,"about_ca_topic_score_gemma":0.00024324005,"teacher_disagreement_score":0.00166228,"about_ca_system_score_codex":0.0001401352,"about_ca_system_score_gemma":0.00027386943,"threshold_uncertainty_score":0.005560875},"labels":[],"label_agreement":null},{"id":"W2148450601","doi":"10.1007/s13534-014-0146-y","title":"Strain ratio vs. modulus ratio for the diagnosis of breast cancer using elastography","year":2014,"lang":"en","type":"article","venue":"Biomedical Engineering Letters","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Grand River Hospital; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Elastography; Malignancy; Modulus; Materials science; Finite element method; Elastic modulus; Stiffness; Ultrasound; Biomedical engineering; Aspect ratio (aeronautics); Composite material; Medicine; Radiology; Pathology; Structural engineering","score_opus":0.00905836195648946,"score_gpt":0.2358729476360206,"score_spread":0.22681458567953114,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2148450601","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.94046056,0.02271324,0.02675736,0.0013265723,0.0002865963,0.000091578884,0.0008690544,0.0006999377,0.00679514],"genre_scores_gemma":[0.9833081,0.002494409,0.012897444,0.00020611263,0.00018204232,0.000040387255,0.00023554654,0.000055324625,0.00058054633],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9978416,0.0009395834,0.00023950715,0.00030638868,0.0005237772,0.00014920093],"domain_scores_gemma":[0.9805149,0.016357074,0.0011816588,0.0005520781,0.001031404,0.00036290483],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006192315,0.000999159,0.0011531662,0.004672794,0.0003604579,0.00187874,0.00093193335,0.0022754981,0.0026200972],"category_scores_gemma":[0.020627467,0.0006706895,0.0005984352,0.0018722998,0.00080155063,0.0015178488,0.00083833875,0.0013486127,0.0015428829],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.014042411,0.00050129637,0.57712597,0.0010147709,0.00057621533,0.0021317706,0.0005150722,0.009387522,0.18052796,0.0013960081,0.0013553719,0.21142565],"study_design_scores_gemma":[0.00029657237,0.0043127663,0.5729423,0.00046175288,0.0021940207,0.018889623,0.0017587016,0.26125655,0.12731583,0.0066227787,0.0036327213,0.0003163938],"about_ca_topic_score_codex":0.00051379023,"about_ca_topic_score_gemma":0.0006773921,"teacher_disagreement_score":0.006192315,"about_ca_system_score_codex":0.0002471445,"about_ca_system_score_gemma":0.00026550202,"threshold_uncertainty_score":0.03274846},"labels":[],"label_agreement":null},{"id":"W2573495159","doi":"10.1007/s13534-017-0010-y","title":"Rheological study of hyaluronic acid derivatives","year":2017,"lang":"en","type":"article","venue":"Biomedical Engineering Letters","topic":"Proteoglycans and glycosaminoglycans research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":33,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hyaluronic acid; Viscoelasticity; Rheology; Chemistry; Viscosity; Derivative (finance); Polymer chemistry; Nuclear chemistry; Materials science; Composite material; Medicine; Anatomy","score_opus":0.014889042453583417,"score_gpt":0.2722666103261681,"score_spread":0.2573775678725847,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2573495159","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99672794,0.0007782938,0.00052099867,0.000026423882,0.000011724285,0.0000063556204,0.00009823601,0.000007928389,0.0018219218],"genre_scores_gemma":[0.9975501,0.00029281672,0.0003133419,0.00001368274,0.000004362145,0.000003856797,0.00009184708,0.0000065273307,0.001723444],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9999236,0.000013622106,0.0000070194797,0.000012466097,0.000024416979,0.000018805607],"domain_scores_gemma":[0.99986625,0.000034149267,0.00003171862,0.000011327929,0.00003247294,0.000024131541],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00011469962,0.00016559387,0.00009442947,0.00019962137,0.00012967187,0.00018974654,0.000104466955,0.0001233941,0.0015585641],"category_scores_gemma":[0.00020981528,0.00006267648,0.00011167556,0.00023689914,0.00014853904,0.00017661526,0.00007117106,0.0003006777,0.00015904698],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00015665372,0.00001915546,0.0002680181,0.000029013585,0.000005695374,0.00009535378,0.000045212408,0.00019299542,0.9977081,0.000101763624,0.000031003197,0.001347092],"study_design_scores_gemma":[0.000006445978,0.00013761962,0.003709829,0.0000045424454,0.000009502765,0.00006708158,0.000036570324,0.0010078482,0.9941947,0.000018966286,0.0008008475,0.000006155437],"about_ca_topic_score_codex":0.00064826326,"about_ca_topic_score_gemma":0.00035551572,"teacher_disagreement_score":0.0015585641,"about_ca_system_score_codex":0.00012963565,"about_ca_system_score_gemma":0.00009200416,"threshold_uncertainty_score":0.0052139163},"labels":[],"label_agreement":null},{"id":"W2577511158","doi":"10.1007/s13534-016-0004-1","title":"Adaptive common average reference for in vivo multichannel local field potentials","year":2017,"lang":"en","type":"article","venue":"Biomedical Engineering Letters","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":false,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"","funders":"Concordia University; National Natural Science Foundation of China","keywords":"Computer science; Local field potential; Noise (video); Artificial intelligence; Field (mathematics); Pattern recognition (psychology); Mathematics; Neuroscience","score_opus":0.029377892917320996,"score_gpt":0.2530527138884529,"score_spread":0.22367482097113192,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2577511158","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0140383,0.000544774,0.9835947,0.00010417759,0.000063875785,0.000017206303,0.00008756167,0.00030691066,0.0012424417],"genre_scores_gemma":[0.3063577,0.0009974741,0.68668896,0.00015351563,0.0001343177,0.00008214216,0.00045543213,0.00037609166,0.004754321],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99974185,0.000079233054,0.000013473351,0.00006002052,0.000086190266,0.0000192935],"domain_scores_gemma":[0.99951744,0.00017885808,0.000038849055,0.00009853133,0.00014219612,0.000024207657],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072430406,0.00045243875,0.00037448184,0.0004688292,0.0003310715,0.0006836154,0.00083445635,0.00075118826,0.0017700199],"category_scores_gemma":[0.00265637,0.00021710906,0.00028265212,0.00073559035,0.0003154402,0.001008015,0.00076639245,0.0007833156,0.0006215427],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0005086454,0.00010668316,0.00093506265,0.00029923258,0.000109925626,0.00020210145,0.00027474712,0.09671724,0.22847782,0.03303927,0.006396359,0.6329329],"study_design_scores_gemma":[0.000025955133,0.00010247808,0.0014841575,0.000030380555,0.000044586184,0.00030255868,0.000034681063,0.91777325,0.061957978,0.009934832,0.008270737,0.00003849064],"about_ca_topic_score_codex":0.0022234428,"about_ca_topic_score_gemma":0.004689902,"teacher_disagreement_score":0.0022234428,"about_ca_system_score_codex":0.00030654366,"about_ca_system_score_gemma":0.0005828014,"threshold_uncertainty_score":0.005921304},"labels":[],"label_agreement":null},{"id":"W2591708961","doi":"10.1007/s13534-017-0020-9","title":"Automatic error correction using adaptive weighting for vessel-based deformable image registration","year":2017,"lang":"en","type":"article","venue":"Biomedical Engineering Letters","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Custom Security Industries (Canada); Ontario Tech University","funders":"","keywords":"Weighting; Image registration; Metric (unit); Artificial intelligence; Computer science; Computer vision; Adaptation (eye); Error detection and correction; Image (mathematics); Algorithm; Engineering; Radiology; Optics; Physics; Medicine","score_opus":0.025129942129246685,"score_gpt":0.28403622273370766,"score_spread":0.25890628060446097,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2591708961","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.020768294,0.00019723548,0.9772017,0.000064395645,0.00004668105,0.000042848253,0.000040479994,0.0011701098,0.0004683639],"genre_scores_gemma":[0.1746544,0.0003191668,0.8208856,0.000066341294,0.000028395569,0.00006753951,0.0002509297,0.000859738,0.0028679452],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9990532,0.00016044709,0.000074343574,0.00019354795,0.00042757133,0.00009094018],"domain_scores_gemma":[0.9985061,0.00038287925,0.00020625438,0.000391202,0.0004671589,0.000046318077],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015154572,0.00080287387,0.00086981605,0.001504041,0.0004310166,0.0011780574,0.0014098496,0.0011655537,0.0017774268],"category_scores_gemma":[0.0039281636,0.00067565707,0.00085516536,0.0015130572,0.0004235836,0.001320964,0.0015749765,0.0013153546,0.0008830101],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00037132783,0.00016554934,0.0015573137,0.00023189095,0.00015929731,0.00012199953,0.00025154534,0.043507535,0.32257202,0.00673413,0.002813401,0.6215139],"study_design_scores_gemma":[0.000024143235,0.000106943924,0.0024283114,0.000024072744,0.00009857455,0.0003814165,0.00003931689,0.7958351,0.19197267,0.0031083482,0.005917339,0.000063782805],"about_ca_topic_score_codex":0.0028032935,"about_ca_topic_score_gemma":0.0040073176,"teacher_disagreement_score":0.0028032935,"about_ca_system_score_codex":0.00044290465,"about_ca_system_score_gemma":0.0011698423,"threshold_uncertainty_score":0.008014619},"labels":[],"label_agreement":null},{"id":"W2608543363","doi":"10.1007/s13534-017-0031-6","title":"Non-magnetic compliant finger sensor for continuous fine motor movement detection","year":2017,"lang":"en","type":"article","venue":"Biomedical Engineering Letters","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Fraser Health; Surrey Memorial Hospital; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Down Syndrome Research Foundation","keywords":"Computer science; Movement (music); Channel (broadcasting); Artificial intelligence; Finger tapping; SIGNAL (programming language); Computer vision; Pattern recognition (psychology); Speech recognition; Acoustics; Physics; Telecommunications","score_opus":0.014623709073115682,"score_gpt":0.2336755904874553,"score_spread":0.2190518814143396,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2608543363","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30007383,0.0021998044,0.6836826,0.00057271065,0.0006186316,0.00017638363,0.00054743676,0.0013214608,0.010807091],"genre_scores_gemma":[0.92893076,0.0003407606,0.0643981,0.00038645396,0.000111938694,0.000061861414,0.00014675246,0.0000463462,0.005577063],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9995326,0.00008100004,0.000030462277,0.000101302496,0.00022911992,0.000025552972],"domain_scores_gemma":[0.99951553,0.0001940494,0.00006993424,0.00007530928,0.00011173509,0.000033376407],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00032062546,0.00036840097,0.00032400744,0.00022048627,0.0002095084,0.0004629448,0.00070759887,0.0007014053,0.0020789544],"category_scores_gemma":[0.0010322114,0.0001692538,0.00017838232,0.00027658662,0.00020736977,0.0006188004,0.0004720438,0.0002762506,0.00056695484],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00038344815,0.000089580106,0.0013537382,0.00025252477,0.000024003844,0.00019745636,0.000060181057,0.0006404127,0.89877063,0.0007411944,0.001245315,0.09624153],"study_design_scores_gemma":[0.000091965,0.001588915,0.030973596,0.00008468577,0.00014674621,0.0037784807,0.000103070495,0.09420805,0.8527173,0.0019069308,0.01427673,0.00012349706],"about_ca_topic_score_codex":0.00018844567,"about_ca_topic_score_gemma":0.0007612616,"teacher_disagreement_score":0.0020789544,"about_ca_system_score_codex":0.00013916618,"about_ca_system_score_gemma":0.00020089265,"threshold_uncertainty_score":0.006954789},"labels":[],"label_agreement":null},{"id":"W2610638560","doi":"10.1007/s13534-017-0033-4","title":"Unified principles of thalamo-cortical processing: the neural switch","year":2017,"lang":"en","type":"article","venue":"Biomedical Engineering Letters","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Children's Hospital; Child and Family Research Institute; Simon Fraser University; University of British Columbia; University of British Columbia Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Leading Edge Endowment Fund","keywords":"Neuroscience; Neurophysiology; Neocortex; Psychology; Human brain; Thalamus; Sensory system; Cognition; Information processing; Cognitive science; Computer science","score_opus":0.03268908905070847,"score_gpt":0.24590132924819091,"score_spread":0.21321224019748244,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2610638560","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0855733,0.005392545,0.814919,0.008415826,0.0008776761,0.000048117967,0.0003352763,0.000730615,0.08370767],"genre_scores_gemma":[0.9330479,0.002546528,0.055717565,0.00076244696,0.00059491803,0.00009103304,0.00011805834,0.0002032678,0.006918313],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9997739,0.000048746595,0.000012937434,0.0000647258,0.00006782539,0.00003183569],"domain_scores_gemma":[0.99969876,0.00012411752,0.000023236673,0.000074967706,0.000048103902,0.00003076375],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005738124,0.00032295214,0.0006365323,0.00044661306,0.0004344824,0.002280962,0.0011213638,0.0013899633,0.00390497],"category_scores_gemma":[0.0015162193,0.0002904581,0.00048755793,0.00028062324,0.0021674763,0.0040114135,0.0010834421,0.0014497642,0.00080437947],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000036690577,0.000011520784,0.00016538109,0.000036402962,0.000020575757,0.00007066691,0.00011846506,0.008181019,0.0100855455,0.9668451,0.0013624292,0.013066262],"study_design_scores_gemma":[0.000012111701,0.000013066155,0.00039806205,0.000010588543,0.0000061739634,0.00006213749,0.000035423654,0.036970165,0.0008364385,0.9595324,0.0021091287,0.000014377034],"about_ca_topic_score_codex":0.0004998301,"about_ca_topic_score_gemma":0.00035930306,"teacher_disagreement_score":0.00390497,"about_ca_system_score_codex":0.00050545874,"about_ca_system_score_gemma":0.0003784984,"threshold_uncertainty_score":0.013063431},"labels":[],"label_agreement":null},{"id":"W2761197040","doi":"10.1007/s13534-017-0051-2","title":"Performance of machine learning methods in diagnosing Parkinson’s disease based on dysphonia measures","year":2017,"lang":"en","type":"article","venue":"Biomedical Engineering Letters","topic":"Voice and Speech Disorders","field":"Medicine","cited_by":132,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"","keywords":"Support vector machine; Artificial intelligence; Naive Bayes classifier; Machine learning; Linear discriminant analysis; Mahalanobis distance; Computer science; Receiver operating characteristic; Pattern recognition (psychology); Cross-validation; Artificial neural network; Classifier (UML); Speech recognition","score_opus":0.01618696888090982,"score_gpt":0.2883518000694649,"score_spread":0.2721648311885551,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2761197040","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9615062,0.007338141,0.025369046,0.0005296702,0.0003566736,0.00005390012,0.0007599486,0.0005291058,0.0035572334],"genre_scores_gemma":[0.9904146,0.00065236323,0.0072438503,0.000073469295,0.0000848741,0.000013979735,0.00077229575,0.000024676603,0.00071989035],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99794954,0.0009052695,0.00029006647,0.0003098432,0.00040445174,0.00014086606],"domain_scores_gemma":[0.98291504,0.014637828,0.00040155815,0.0003883672,0.0013569082,0.00030035316],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0058956896,0.0008619648,0.0006707803,0.0018290745,0.00034021278,0.0013039793,0.00046461323,0.0015853166,0.000812136],"category_scores_gemma":[0.015216492,0.00019197822,0.00055615645,0.000514763,0.00031051162,0.0007558153,0.00049960887,0.0005842675,0.000599216],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.010896482,0.0010737145,0.30912372,0.00062015606,0.0016020635,0.00034426758,0.00035424318,0.07209269,0.023245873,0.00062902947,0.0033839615,0.5766338],"study_design_scores_gemma":[0.00018207618,0.0020794864,0.16953191,0.00013258558,0.00054300216,0.0008183398,0.00032957448,0.8034924,0.020471554,0.000883657,0.0014260018,0.00010948712],"about_ca_topic_score_codex":0.00366534,"about_ca_topic_score_gemma":0.0024091136,"teacher_disagreement_score":0.0058956896,"about_ca_system_score_codex":0.00040401905,"about_ca_system_score_gemma":0.00043257044,"threshold_uncertainty_score":0.031179786},"labels":[],"label_agreement":null},{"id":"W2766549125","doi":"10.1007/s13534-017-0052-1","title":"Elastography for portable ultrasound","year":2017,"lang":"en","type":"article","venue":"Biomedical Engineering Letters","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Elastography; Imaging phantom; Ultrasound; Computer science; Estimator; Biomedical engineering; Acoustics; Radiology; Mathematics; Medicine; Physics; Statistics","score_opus":0.00815342789908424,"score_gpt":0.24069331843291356,"score_spread":0.2325398905338293,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2766549125","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.012407814,0.05586589,0.77170277,0.013706015,0.0058441055,0.0001975144,0.00057733426,0.0039972174,0.13570137],"genre_scores_gemma":[0.20981358,0.045915745,0.47732174,0.005447129,0.005903272,0.00037130038,0.0008712127,0.0010083014,0.2533477],"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.999388,0.0001418505,0.00004167689,0.000121222445,0.00027182605,0.000035319285],"domain_scores_gemma":[0.99932075,0.0002625247,0.000048144953,0.00020726536,0.000119122175,0.000042180855],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00041203463,0.00080697244,0.0004930057,0.0008357984,0.00037833952,0.0013547448,0.0009357714,0.001805071,0.02767196],"category_scores_gemma":[0.0014420686,0.00045981578,0.00045784895,0.0006260041,0.0010472025,0.0017307106,0.0016754303,0.0018860095,0.01290549],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00016615108,0.000073120034,0.00070442795,0.0011455244,0.000037434955,0.0022212989,0.00028835182,0.0024579894,0.1620219,0.14924805,0.05660157,0.6250342],"study_design_scores_gemma":[0.000041127423,0.00023306317,0.0018393885,0.0005318433,0.000047703914,0.012942998,0.00014348915,0.017824726,0.091227785,0.075519815,0.79953825,0.00010983579],"about_ca_topic_score_codex":0.00016082835,"about_ca_topic_score_gemma":0.00028082557,"teacher_disagreement_score":0.02767196,"about_ca_system_score_codex":0.00032570586,"about_ca_system_score_gemma":0.0002610188,"threshold_uncertainty_score":0.092571914},"labels":[],"label_agreement":null},{"id":"W2788193492","doi":"10.1007/s13534-018-0057-4","title":"Increasing the quality of reconstructed signal in compressive sensing utilizing Kronecker technique","year":2018,"lang":"en","type":"article","venue":"Biomedical Engineering Letters","topic":"Sparse and Compressive Sensing Techniques","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Carleton University","funders":"","keywords":"Compressed sensing; Mutual coherence; Kronecker product; Kronecker delta; Algorithm; Computer science; Signal reconstruction; Dimension (graph theory); Projection (relational algebra); Coherence (philosophical gambling strategy); SIGNAL (programming language); Matrix (chemical analysis); Computation; Basis (linear algebra); Signal processing; Reconstruction algorithm; Pattern recognition (psychology); Iterative reconstruction; Artificial intelligence; Mathematics; Digital signal processing","score_opus":0.01869927732432641,"score_gpt":0.24907960567906395,"score_spread":0.23038032835473754,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2788193492","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08254626,0.0005425788,0.91259176,0.0004341017,0.000096608645,0.00002590074,0.00006166394,0.0002088638,0.003492216],"genre_scores_gemma":[0.64058465,0.0012162906,0.3548043,0.00021735871,0.00010779757,0.000027464941,0.00013199198,0.00006376157,0.002846301],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993376,0.00021931656,0.000037359147,0.00007091786,0.00029795634,0.000036781177],"domain_scores_gemma":[0.99760395,0.0012191447,0.00021843097,0.0003266179,0.000549985,0.000081787824],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011563072,0.00053917733,0.00034608383,0.0004047818,0.00016466585,0.0005642809,0.00032082453,0.0007382808,0.0015766728],"category_scores_gemma":[0.004913298,0.0002203831,0.00023009129,0.000490314,0.0006722961,0.0013251272,0.0008377889,0.00073970936,0.00030284375],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0010549554,0.00022145768,0.0029398664,0.00057855295,0.00010783714,0.00038836835,0.00034427716,0.16937475,0.42210037,0.056353234,0.002400676,0.34413564],"study_design_scores_gemma":[0.000038214766,0.0004416662,0.0017844205,0.00005917747,0.000042262796,0.0005625638,0.00009464996,0.8902352,0.09309611,0.011570055,0.0020209474,0.000054850287],"about_ca_topic_score_codex":0.00037463557,"about_ca_topic_score_gemma":0.00063017017,"teacher_disagreement_score":0.0015766728,"about_ca_system_score_codex":0.0001615261,"about_ca_system_score_gemma":0.00034761743,"threshold_uncertainty_score":0.006115198},"labels":[],"label_agreement":null},{"id":"W2795664372","doi":"10.1007/s13534-018-0063-6","title":"Surface morphology characterization of laser-induced titanium implants: lesson to enhance osseointegration process","year":2018,"lang":"en","type":"article","venue":"Biomedical Engineering Letters","topic":"Laser Applications in Dentistry and Medicine","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Osseointegration; Kurtosis; Titanium; Materials science; Laser; Surface (topology); Characterization (materials science); Texture (cosmology); Morphology (biology); Root mean square; Implant; Composite material; Mathematics; Optics; Geometry; Nanotechnology; Medicine; Image (mathematics); Physics; Computer science","score_opus":0.0099218587681763,"score_gpt":0.2962819484746558,"score_spread":0.28636008970647947,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2795664372","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9599598,0.005162393,0.027661402,0.0012352009,0.00027385983,0.00006625139,0.00015253341,0.00023477005,0.005253743],"genre_scores_gemma":[0.982464,0.0013899262,0.012034604,0.00021068408,0.00006040115,0.000024425297,0.0001079573,0.00008501575,0.0036229377],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99974376,0.000029552533,0.000014583066,0.000044921835,0.00013010333,0.000037083653],"domain_scores_gemma":[0.99970764,0.000053706855,0.000047167832,0.000037136215,0.00013592285,0.000018285056],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027232256,0.0002570025,0.0002264618,0.00027769295,0.00021114743,0.00047143805,0.0003276377,0.00069982884,0.0015193889],"category_scores_gemma":[0.00053461565,0.00022000246,0.0003259115,0.000246393,0.00028127976,0.0006584254,0.00019557323,0.0005345716,0.0005068417],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000040181116,0.000018377774,0.0005576234,0.000058322516,0.0000045695188,0.00004342734,0.00005783306,0.000087449655,0.9913089,0.00011467524,0.00014968058,0.0075588254],"study_design_scores_gemma":[0.000010971735,0.00028874175,0.009809708,0.000010647859,0.00002661461,0.0003249186,0.00016795672,0.0026021276,0.98247784,0.0002562356,0.004005541,0.000018659794],"about_ca_topic_score_codex":0.00035976543,"about_ca_topic_score_gemma":0.0007567223,"teacher_disagreement_score":0.0015193889,"about_ca_system_score_codex":0.00023021702,"about_ca_system_score_gemma":0.00016793417,"threshold_uncertainty_score":0.0050828457},"labels":[],"label_agreement":null},{"id":"W2950075737","doi":"10.1007/s13534-019-00116-w","title":"A multiscale Mueller polarimetry module for a stereo zoom microscope","year":2019,"lang":"en","type":"article","venue":"Biomedical Engineering Letters","topic":"Optical Polarization and Ellipsometry","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network; University of Toronto","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; National Institutes of Health; National Cancer Institute; Canadian Institutes of Health Research; National Institute of General Medical Sciences; University of Wisconsin Carbone Cancer Center","keywords":"Polarimetry; Zoom; Computer science; Microscope; Computer vision; Scanning laser polarimetry; Visualization; Mueller calculus; Artificial intelligence; Optics; Physics; Optical coherence tomography","score_opus":0.0038725660205391464,"score_gpt":0.18556749353592034,"score_spread":0.1816949275153812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2950075737","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.046191502,0.00012104919,0.9070458,0.00014502497,0.00007092118,0.00028048322,0.0021228138,0.03879057,0.00523179],"genre_scores_gemma":[0.18434235,0.00014159907,0.7977828,0.00027538373,0.000055145443,0.00056600594,0.0030819965,0.0038952096,0.009859431],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99970835,0.000012726965,0.000012980741,0.000058754344,0.00017581267,0.000031372067],"domain_scores_gemma":[0.9995962,0.00009812254,0.000033509295,0.00009861486,0.0001358117,0.000037756367],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00038556138,0.00056165754,0.0004642856,0.0007388273,0.00027454706,0.0004519941,0.0009112778,0.0004108895,0.018453082],"category_scores_gemma":[0.0006516873,0.00050104986,0.00037115236,0.00036456765,0.0001245974,0.0006129818,0.0009731612,0.00052136264,0.0036334463],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00024398915,0.00015491982,0.0026009406,0.00019991754,0.00007981369,0.00013308352,0.00014990407,0.0026314666,0.7903972,0.0036427889,0.014315314,0.18545067],"study_design_scores_gemma":[0.00009473732,0.0002175554,0.011142167,0.000043209217,0.00007101719,0.00079170003,0.00006383923,0.16057858,0.7703935,0.0023389254,0.05413729,0.0001275067],"about_ca_topic_score_codex":0.00082142884,"about_ca_topic_score_gemma":0.0018947057,"teacher_disagreement_score":0.018453082,"about_ca_system_score_codex":0.0003356031,"about_ca_system_score_gemma":0.00052210834,"threshold_uncertainty_score":0.061731756},"labels":[],"label_agreement":null},{"id":"W2966692255","doi":"10.1007/s13534-019-00125-9","title":"Photon mayhem: new directions in diagnostic and therapeutic photomedicine","year":2019,"lang":"en","type":"editorial","venue":"Biomedical Engineering Letters","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; University Health Network","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Science and ICT, South Korea; National Research Foundation of Korea; Gwangju Institute of Science and Technology; Canadian Institutes of Health Research; National Research Foundation","keywords":"Intensive care medicine; Medicine; Physics","score_opus":0.004770677339103307,"score_gpt":0.21040610806575544,"score_spread":0.20563543072665214,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2966692255","genre_codex":"editorial","genre_gemma":"editorial","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"editorial","genre_consensus":"editorial","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000035889385,0.012251406,0.00021762296,0.03774496,0.9478257,0.000017812135,0.000023120672,0.000045563724,0.0018379614],"genre_scores_gemma":[0.0004564221,0.0066217473,0.00015277884,0.021497598,0.96156496,0.00001504288,0.000012695021,0.000022976315,0.009655736],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9934882,0.001333295,0.0007201647,0.0005568821,0.0035271875,0.00037428754],"domain_scores_gemma":[0.98420924,0.0071840314,0.0009304473,0.0004528795,0.0050790454,0.002144365],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007951362,0.003903247,0.003314818,0.004156321,0.003195943,0.008806316,0.0043186415,0.02534394,0.010800791],"category_scores_gemma":[0.018604117,0.0015516534,0.0029433332,0.0013137426,0.0033328815,0.005135341,0.0023459843,0.02496664,0.0073156483],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006277565,0.000019655143,0.000021633961,0.00033131134,0.000026438498,0.00017472138,0.0000125542065,0.000039231207,0.0001391102,0.0008545499,0.988182,0.010135927],"study_design_scores_gemma":[0.000053999975,0.000032268697,0.00018038244,0.00022712063,0.000054693963,0.00029328314,0.000026091871,0.00022422042,0.00016668353,0.0018545977,0.9968671,0.000019510011],"about_ca_topic_score_codex":0.0014486216,"about_ca_topic_score_gemma":0.005117374,"teacher_disagreement_score":0.02534394,"about_ca_system_score_codex":0.0042787855,"about_ca_system_score_gemma":0.0026994299,"threshold_uncertainty_score":0.042051315},"labels":[],"label_agreement":null},{"id":"W2997354144","doi":"10.1007/s13534-019-00143-7","title":"Correction to: A multiscale Mueller polarimetry module for a stereo zoom microscope","year":2020,"lang":"en","type":"erratum","venue":"Biomedical Engineering Letters","topic":"Optical Polarization and Ellipsometry","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Princess Margaret Cancer Centre; University Health Network; University of Toronto","funders":"","keywords":"Zoom; Polarimetry; Microscope; Computer science; Optics; Artificial intelligence; Computer vision; Physics","score_opus":0.007288817195031823,"score_gpt":0.21112089904526368,"score_spread":0.20383208185023186,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2997354144","genre_codex":"editorial","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0026028773,0.0017536705,0.030302847,0.035007562,0.8795695,0.00023054268,0.0077231885,0.01818075,0.02462913],"genre_scores_gemma":[0.04419054,0.0027717284,0.10365588,0.026745994,0.04076302,0.00044093435,0.010535099,0.014581161,0.75631577],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9973568,0.00018846855,0.00029346696,0.00032603566,0.0016057269,0.00022949299],"domain_scores_gemma":[0.98627394,0.0017990248,0.0005254839,0.0014837193,0.00944801,0.00046977834],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012321813,0.0025521466,0.0012117208,0.004474527,0.0033138776,0.002663075,0.0024518322,0.0045595123,0.21372107],"category_scores_gemma":[0.017806891,0.0014179217,0.0013452907,0.002392662,0.0013163314,0.002320697,0.0024932188,0.004798222,0.07427844],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00006537522,0.000012078078,0.00010812898,0.00013976244,0.000009540788,0.00017392174,0.000028736677,0.00018404676,0.0012261361,0.0016215264,0.9745276,0.021903194],"study_design_scores_gemma":[0.000041641153,0.000025474032,0.0012546295,0.0001067511,0.000024387135,0.00065278704,0.000078983125,0.002889536,0.005527555,0.0023749915,0.9869551,0.00006811836],"about_ca_topic_score_codex":0.01859411,"about_ca_topic_score_gemma":0.03730539,"teacher_disagreement_score":0.21372107,"about_ca_system_score_codex":0.0037554584,"about_ca_system_score_gemma":0.0033780814,"threshold_uncertainty_score":0.7149682},"labels":[],"label_agreement":null},{"id":"W3196879561","doi":"10.1007/s13534-021-00206-8","title":"Micro/nanotechnology-inspired rapid diagnosis of respiratory infectious diseases","year":2021,"lang":"en","type":"review","venue":"Biomedical Engineering Letters","topic":"Respiratory viral infections research","field":"Medicine","cited_by":13,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nanodevice; Nanotechnology; Infectious disease (medical specialty); Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Software portability; Diagnostic test; Computer science; Risk analysis (engineering); Medicine; Intensive care medicine; Disease; Materials science; Pathology","score_opus":0.0375728791085567,"score_gpt":0.3307798614305125,"score_spread":0.2932069823219558,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3196879561","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00010593349,0.9983919,0.00018254995,0.00016872003,0.00030772522,0.0000036206159,0.00000865454,0.0000063204548,0.00082454016],"genre_scores_gemma":[0.0009251395,0.9975266,0.00023476471,0.00020119039,0.0002457293,0.0000050001763,0.000015405154,0.0000012832271,0.00084483664],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998437,0.000022977043,0.0000131916995,0.000027489588,0.00006931812,0.000023137696],"domain_scores_gemma":[0.999767,0.00011348761,0.000031253203,0.0000072065427,0.000057525336,0.000023485785],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000508344,0.00094840303,0.0010789806,0.0013101178,0.00018736781,0.00087662967,0.0006819389,0.0010942233,0.002484417],"category_scores_gemma":[0.0006345559,0.0003141461,0.00036098712,0.0011458189,0.0004445416,0.0009962497,0.00067009695,0.0014921267,0.001818241],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000081372025,0.000067126966,0.000098742916,0.015013827,0.00006596939,0.00014114557,0.00004126968,0.0003413081,0.007315236,0.0052190064,0.034004185,0.9376107],"study_design_scores_gemma":[0.000019384552,0.00011625463,0.00046230573,0.0020527034,0.000090921654,0.0006256539,0.000034465236,0.00024698055,0.0028355767,0.0016439976,0.99185,0.000021798482],"about_ca_topic_score_codex":0.000867561,"about_ca_topic_score_gemma":0.0020577768,"teacher_disagreement_score":0.002484417,"about_ca_system_score_codex":0.0005442867,"about_ca_system_score_gemma":0.00075397984,"threshold_uncertainty_score":0.008311212},"labels":[],"label_agreement":null},{"id":"W4224278107","doi":"10.1007/s13534-022-00226-y","title":"Deep brain stimulation for Parkinson’s Disease: A Review and Future Outlook","year":2022,"lang":"en","type":"review","venue":"Biomedical Engineering Letters","topic":"Neurological disorders and treatments","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ottawa Hospital; University of Ottawa","funders":"","keywords":"Deep brain stimulation; Parkinson's disease; Neuroscience; Motor symptoms; Disease; Medicine; Physical medicine and rehabilitation; Brain stimulation; Dopamine; Stimulation; Psychology; Internal medicine","score_opus":0.022872976866301558,"score_gpt":0.2892185398501385,"score_spread":0.26634556298383694,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4224278107","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009723403,0.9991385,0.000099183104,0.00016709199,0.00012038525,0.0000045169077,0.0000128342,0.000004330396,0.00035591805],"genre_scores_gemma":[0.00064199616,0.9984493,0.00018199028,0.00026471424,0.00016877496,0.0000072425146,0.000019023288,0.0000011172591,0.00026583977],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998734,0.000022576573,0.000026722482,0.00002844569,0.000033914213,0.000014846814],"domain_scores_gemma":[0.99968314,0.00018396541,0.000048778675,0.0000056759773,0.00005346525,0.00002494514],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00063666346,0.00092944386,0.0016139323,0.0013879746,0.00016560762,0.0010655356,0.00079827604,0.0012580707,0.0038047927],"category_scores_gemma":[0.0006786188,0.00026390527,0.0006682331,0.0014287804,0.0004310304,0.0011779458,0.00058862363,0.0016165698,0.001367609],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00020316607,0.00009781996,0.0001132109,0.031407088,0.00020384669,0.00016920449,0.000049757655,0.00035152392,0.0024407508,0.0016224773,0.020852026,0.9424892],"study_design_scores_gemma":[0.00024452445,0.00069495634,0.0019094213,0.013540599,0.00094126456,0.0025326256,0.00014145162,0.00046708935,0.0010304519,0.0032512671,0.975172,0.00007429655],"about_ca_topic_score_codex":0.0008146441,"about_ca_topic_score_gemma":0.002347679,"teacher_disagreement_score":0.0038047927,"about_ca_system_score_codex":0.000380646,"about_ca_system_score_gemma":0.0008829037,"threshold_uncertainty_score":0.0127283335},"labels":[],"label_agreement":null},{"id":"W4254316491","doi":"10.1007/s13534-014-0126-2","title":"Optimal selection of regularization parameter in total variation method for reducing noise in magnetic resonance images of the brain","year":2014,"lang":"en","type":"article","venue":"Biomedical Engineering Letters","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"NeuroRx Research (Canada); Concordia University","funders":"National Institute of Biomedical Imaging and Bioengineering","keywords":"Regularization (linguistics); Total variation denoising; Computer science; Noise reduction; Algorithm; Mathematical optimization; Mathematics; Artificial intelligence","score_opus":0.005796463162876957,"score_gpt":0.23092624915753293,"score_spread":0.22512978599465597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4254316491","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025202235,0.00059715443,0.9732762,0.00015732697,0.000044797922,0.000027444028,0.000026766596,0.00024192712,0.00042613846],"genre_scores_gemma":[0.26185313,0.0006103441,0.735158,0.00013050479,0.00007172204,0.00015139196,0.00018927046,0.00040559008,0.0014300086],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993259,0.00031504955,0.000044862652,0.00012599284,0.00013414171,0.000054038468],"domain_scores_gemma":[0.9992003,0.000390058,0.000056389752,0.00005548883,0.00026229635,0.0000355776],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016446938,0.0008110521,0.00085434393,0.00074499525,0.00038112365,0.00066924683,0.000975257,0.0015802935,0.00056441646],"category_scores_gemma":[0.003873168,0.00036928497,0.0008123407,0.00047648157,0.0005829948,0.00075773866,0.000618038,0.0008995728,0.00022666788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000846473,0.00048071487,0.0016753838,0.00068348093,0.00033471888,0.0002768422,0.00033965224,0.35893875,0.20503803,0.019537535,0.005286505,0.40656194],"study_design_scores_gemma":[0.00002294633,0.000066719986,0.00047678218,0.000019852314,0.000042265783,0.000058849084,0.000016083704,0.9824692,0.013891233,0.0021556215,0.0007594239,0.000020968704],"about_ca_topic_score_codex":0.0024981664,"about_ca_topic_score_gemma":0.0028110284,"teacher_disagreement_score":0.0024981664,"about_ca_system_score_codex":0.00041112828,"about_ca_system_score_gemma":0.0010618798,"threshold_uncertainty_score":0.008698106},"labels":[],"label_agreement":null},{"id":"W4308518073","doi":"10.1007/s13534-022-00250-y","title":"Deep learning prediction of non-perfused volume without contrast agents during prostate ablation therapy","year":2022,"lang":"en","type":"article","venue":"Biomedical Engineering Letters","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Profound Medical (Canada)","funders":"","keywords":"Prostate cancer; Prostate; Medicine; Ablation; Magnetic resonance imaging; Contrast (vision); Nuclear medicine; Radiology; Ablation zone; Ground truth; Artificial intelligence; Internal medicine; Computer science; Cancer","score_opus":0.007141313450205216,"score_gpt":0.23369290041654306,"score_spread":0.22655158696633784,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4308518073","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7792426,0.00062015007,0.21726227,0.00034636824,0.00004950696,0.00007342021,0.00035118553,0.00073563366,0.0013188676],"genre_scores_gemma":[0.98811615,0.00007124099,0.010765777,0.000052143445,0.000008119935,0.000032467848,0.00020057274,0.000017966155,0.0007355365],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99985874,0.000033778408,0.0000080117425,0.000041919964,0.000030564886,0.00002707447],"domain_scores_gemma":[0.9995721,0.0002522196,0.000052050535,0.000024678739,0.00007318759,0.000025749468],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000516178,0.0004894933,0.0005114524,0.0002787755,0.00013832978,0.00050742034,0.00055401394,0.0006013093,0.0005279054],"category_scores_gemma":[0.0014065893,0.00026079293,0.0005469655,0.00017834119,0.00021788113,0.00034540726,0.00031151978,0.0006087721,0.00012967967],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017451475,0.00008354293,0.008464097,0.00002514579,0.000040306975,0.000090220994,0.000019732508,0.9497185,0.005067858,0.0001807257,0.00041796733,0.03571731],"study_design_scores_gemma":[0.0000021081598,0.000021684802,0.0005275766,0.0000013366825,0.000002871793,0.000007457358,0.0000016890904,0.99827385,0.0010439279,0.00008213376,0.000033590368,0.00000173368],"about_ca_topic_score_codex":0.010615537,"about_ca_topic_score_gemma":0.007467331,"teacher_disagreement_score":0.010615537,"about_ca_system_score_codex":0.0008616894,"about_ca_system_score_gemma":0.00072093355,"threshold_uncertainty_score":0.021107495},"labels":[],"label_agreement":null},{"id":"W4313319102","doi":"10.1007/s13534-022-00259-3","title":"Closed-loop optimal and automatic tuning of pulse amplitude and width in EMG-guided controllable transcranial magnetic stimulation","year":2022,"lang":"en","type":"article","venue":"Biomedical Engineering Letters","topic":"Transcranial Magnetic Stimulation Studies","field":"Neuroscience","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Transcranial magnetic stimulation; Amplitude; Pulse (music); Pulse-width modulation; Pulse-amplitude modulation; Control theory (sociology); Maximization; Constant (computer programming); Time constant; Mathematics; Physics; Computer science; Optics; Mathematical optimization; Artificial intelligence; Stimulation; Engineering; Detector; Voltage","score_opus":0.016127873514251753,"score_gpt":0.23386560370101467,"score_spread":0.2177377301867629,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4313319102","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.3468496,0.0008815824,0.6467118,0.00014785375,0.00009988983,0.00008784799,0.00005484615,0.000640288,0.0045262645],"genre_scores_gemma":[0.9818871,0.00006267808,0.017588539,0.000025532956,0.000008957673,0.000018829642,0.000008752956,0.000021936665,0.00037758125],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9997491,0.000059616945,0.000016267091,0.00007453135,0.00007721314,0.000023263432],"domain_scores_gemma":[0.99958974,0.00027520704,0.00005295724,0.000019519577,0.000048160207,0.000014446836],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00024902992,0.00030484077,0.0001951353,0.00014658397,0.00015563515,0.00036115406,0.00032353948,0.00034128348,0.0005784505],"category_scores_gemma":[0.0014031642,0.00013734862,0.00009711874,0.00013571554,0.00020873277,0.00022716506,0.0002101418,0.00021137486,0.00011342415],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0009820175,0.00017030488,0.00086204265,0.0002415735,0.000035022844,0.00011034746,0.00022481338,0.015470396,0.7643955,0.0015337163,0.00042233305,0.21555206],"study_design_scores_gemma":[0.00022711328,0.0009453249,0.015082124,0.00006717522,0.00008349232,0.0007481085,0.000078808975,0.6158676,0.3613052,0.0024792715,0.0030424017,0.00007333975],"about_ca_topic_score_codex":0.0005227343,"about_ca_topic_score_gemma":0.0009622698,"teacher_disagreement_score":0.0005784505,"about_ca_system_score_codex":0.00013080658,"about_ca_system_score_gemma":0.00016279554,"threshold_uncertainty_score":0.0019351244},"labels":[],"label_agreement":null},{"id":"W4378213174","doi":"10.1007/s13534-023-00286-8","title":"Intracortical brain-computer interfaces in primates: a review and outlook","year":2023,"lang":"en","type":"review","venue":"Biomedical Engineering Letters","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ottawa Hospital; University of Ottawa","funders":"","keywords":"Brain–computer interface; Neuroscience; Physical medicine and rehabilitation; Computer science; Cognitive science; Psychology; Human–computer interaction; Medicine; Electroencephalography","score_opus":0.037143371700508056,"score_gpt":0.3089346076034012,"score_spread":0.2717912359028931,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4378213174","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00009479327,0.9988753,0.00018961684,0.00015854537,0.00012975374,0.000004026584,0.000016047661,0.0000060944208,0.00052577193],"genre_scores_gemma":[0.0005275098,0.9983303,0.00032599305,0.0001940329,0.00026354296,0.0000067580518,0.00002606009,0.0000016738265,0.00032419458],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9998318,0.000022913246,0.000035366083,0.000044833858,0.000048958285,0.000016011147],"domain_scores_gemma":[0.99930906,0.00038161626,0.00008515598,0.000016930599,0.00015781962,0.000049362676],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00087917893,0.0012497505,0.0018178973,0.002903394,0.0002815862,0.0014989319,0.0011672721,0.0015926469,0.0031957077],"category_scores_gemma":[0.0010940337,0.0004150037,0.0006145507,0.0029160536,0.0006495973,0.0020658053,0.00078553305,0.0015967458,0.0023474556],"study_design_candidate":"not_applicable","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0001257294,0.000097153745,0.00021569265,0.022680247,0.00010923934,0.000197286,0.000053504293,0.00031878887,0.001974826,0.0022810241,0.016805694,0.9551409],"study_design_scores_gemma":[0.000062726845,0.00035572375,0.0020060707,0.009981897,0.0004665553,0.0024614325,0.00015656988,0.00029489267,0.0013974431,0.0044561685,0.97829187,0.00006864105],"about_ca_topic_score_codex":0.0012615744,"about_ca_topic_score_gemma":0.0022234037,"teacher_disagreement_score":0.0031957077,"about_ca_system_score_codex":0.0005429345,"about_ca_system_score_gemma":0.0014477685,"threshold_uncertainty_score":0.010690689},"labels":[],"label_agreement":null},{"id":"W4386212195","doi":"10.1007/s13534-023-00313-8","title":"Undersampling and cumulative class re-decision methods to improve detection of agitation in people with dementia","year":2023,"lang":"en","type":"article","venue":"Biomedical Engineering Letters","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Toronto Metropolitan University; University Health Network; Toronto Rehabilitation Institute; University of Toronto","funders":"Alzheimer's Association","keywords":"Undersampling; Dementia; Class (philosophy); Medicine; Computer science; Artificial intelligence; Internal medicine","score_opus":0.025640303877811226,"score_gpt":0.33525804201335424,"score_spread":0.309617738135543,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4386212195","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6771478,0.0047966707,0.31294063,0.0011059932,0.0007899912,0.00015073176,0.00031308184,0.0011825494,0.0015725585],"genre_scores_gemma":[0.9364393,0.00040062465,0.060567442,0.00037986305,0.000253948,0.000054823762,0.0005270729,0.000064026804,0.0013129545],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9988129,0.00054516137,0.00008902656,0.00025257855,0.00018867495,0.00011159576],"domain_scores_gemma":[0.99430954,0.004065477,0.00017393634,0.0003274942,0.0009758587,0.00014767234],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003704744,0.00064883806,0.0011449778,0.00078397687,0.00049711135,0.00069648284,0.0008109996,0.00095010025,0.0008353267],"category_scores_gemma":[0.010286495,0.00021270069,0.0007191086,0.00035072918,0.00033827228,0.00069318747,0.00074610405,0.0012476667,0.0002890341],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.003505466,0.00089297275,0.039895624,0.00015524778,0.000627603,0.0002226848,0.00046614552,0.050753433,0.016630843,0.0015053024,0.0076832417,0.8776614],"study_design_scores_gemma":[0.00006174661,0.00028443747,0.020482203,0.000022793884,0.00013296284,0.00015789246,0.000106981795,0.9712337,0.0050223917,0.0016583884,0.00080146565,0.000034938508],"about_ca_topic_score_codex":0.008627461,"about_ca_topic_score_gemma":0.012035797,"teacher_disagreement_score":0.008627461,"about_ca_system_score_codex":0.00047186227,"about_ca_system_score_gemma":0.0006911343,"threshold_uncertainty_score":0.019592762},"labels":[],"label_agreement":null},{"id":"W4391932769","doi":"10.1007/s13534-024-00353-8","title":"Distal planar rotary scanner for endoscopic optical coherence tomography","year":2024,"lang":"en","type":"article","venue":"Biomedical Engineering Letters","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Cancer Agency; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia","keywords":"Optical coherence tomography; Scanner; Planar; Tomography; Optics; Physics; Computer science; Computer graphics (images)","score_opus":0.006440255764899144,"score_gpt":0.20806016607952615,"score_spread":0.201619910314627,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4391932769","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.2873174,0.00747593,0.6723238,0.0035226706,0.0007645461,0.00030021285,0.000650136,0.004279641,0.023365567],"genre_scores_gemma":[0.64424586,0.0013500841,0.34352624,0.0010582368,0.00022628496,0.0001176971,0.00037560516,0.0003225468,0.008777495],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99945325,0.00010241892,0.000034738478,0.00012319667,0.00022012378,0.00006619653],"domain_scores_gemma":[0.9992085,0.00030433107,0.00008654911,0.00019158023,0.00013818101,0.00007084894],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00056299556,0.0005276934,0.00038027586,0.00047848493,0.0003701499,0.00078347314,0.00073166064,0.0009959751,0.006012503],"category_scores_gemma":[0.0014188483,0.000553035,0.00038231266,0.0003375986,0.0005458999,0.0011006178,0.0011064686,0.001231942,0.0018178584],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.001161865,0.000054176337,0.0025699534,0.00031625258,0.00003000279,0.0011071794,0.00014419825,0.0007458804,0.90821284,0.0033874698,0.0049076164,0.07736256],"study_design_scores_gemma":[0.0004076369,0.0031844538,0.015055932,0.00016407482,0.00031885394,0.05967766,0.00032871266,0.0458466,0.7794733,0.0025914744,0.09254686,0.00040452246],"about_ca_topic_score_codex":0.0003619301,"about_ca_topic_score_gemma":0.0007276297,"teacher_disagreement_score":0.006012503,"about_ca_system_score_codex":0.0002792213,"about_ca_system_score_gemma":0.0007853186,"threshold_uncertainty_score":0.020113826},"labels":[],"label_agreement":null},{"id":"W4393318351","doi":"10.1007/s13534-024-00368-1","title":"3D printing redefines microneedle fabrication for transdermal drug delivery","year":2024,"lang":"en","type":"article","venue":"Biomedical Engineering Letters","topic":"Advancements in Transdermal Drug Delivery","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Saskatchewan","funders":"Beijing Institute of Technology Research Fund Program for Young Scholars; Beijing Institute of Technology","keywords":"Transdermal; Drug administration; 3D printing; Drug delivery; Nanotechnology; Fabrication; Materials science; Biomedical engineering; 3d printed; Process (computing); Medicine; Computer science; Pharmacology; Composite material","score_opus":0.0403309907301287,"score_gpt":0.35191709032607815,"score_spread":0.31158609959594946,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4393318351","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.5797386,0.013930705,0.32004157,0.0020123792,0.0027306958,0.00015005025,0.0012483107,0.0065551675,0.07359253],"genre_scores_gemma":[0.8404724,0.003841557,0.13434714,0.0006367787,0.00014714609,0.000091792164,0.00037848548,0.00071133056,0.019373309],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9996371,0.00002216972,0.00002393979,0.00006187696,0.00021309363,0.000041850762],"domain_scores_gemma":[0.99967957,0.0001245851,0.00006254616,0.00007726286,0.000043242402,0.000012811207],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00026016313,0.00034195438,0.00029067835,0.0003224365,0.00023655404,0.0007240902,0.00036762215,0.0010075197,0.0027558554],"category_scores_gemma":[0.00047277551,0.00035673098,0.00035204168,0.0002483231,0.00039858735,0.0004878994,0.00050045917,0.0007898415,0.0016216262],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000023651337,0.00001190134,0.00007504912,0.00011122841,0.0000055009177,0.00016095166,0.00006118867,0.0010085445,0.97875893,0.0011211876,0.0007605273,0.017901275],"study_design_scores_gemma":[0.0000050529343,0.000040844214,0.0006009705,0.00001434322,0.0000076109163,0.00031012733,0.000014877425,0.0038993151,0.9807873,0.0003406703,0.013959931,0.00001891437],"about_ca_topic_score_codex":0.00039114547,"about_ca_topic_score_gemma":0.0011114706,"teacher_disagreement_score":0.0027558554,"about_ca_system_score_codex":0.00040563213,"about_ca_system_score_gemma":0.00024500434,"threshold_uncertainty_score":0.009219229},"labels":[],"label_agreement":null}]}