{"id":"W4398362790","doi":"10.7910/dvn/bxiy5w/wjpfdk","title":"GRAY_2017.RData","year":2019,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Vector Institute; Princess Margaret Cancer Centre","funders":"","keywords":"Gray (unit); Computer science; Medicine; Nuclear medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009862267,0.003426129,0.001468334,0.003998681,0.0009253399,0.002332,0.002813153,0.002124821,0.1079864],"category_scores_gemma":[0.00369764,0.001159229,0.001747792,0.004342796,0.0006197364,0.00155771,0.002586017,0.001965238,0.1244223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001753521,"about_ca_system_score_gemma":0.002648404,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01924263,"about_ca_topic_score_gemma":0.03230043,"domain_scores_codex":[0.9990994,0.0001030655,0.0001014212,0.000292136,0.0002530267,0.0001509448],"domain_scores_gemma":[0.9987012,0.0003388652,0.0001048792,0.0003952155,0.0002666908,0.000193061],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000103831,0.00003714466,0.0005423318,0.0005533512,0.00003301677,0.00002666347,0.00002434776,0.0003713579,0.0003201507,0.0006396355,0.9942913,0.003056868],"study_design_scores_gemma":[0.0004092411,0.00002576451,0.001861025,0.0001616924,0.00003955023,0.00006604672,0.00005181526,0.0009223992,0.001143605,0.001628429,0.993656,0.00003451762],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001976657,0.0000594003,0.0001226159,0.00007387842,0.00003392337,0.00001744851,0.9967071,0.001633202,0.001154731],"genre_scores_gemma":[0.0005007759,0.0000688314,0.0004152914,0.00007510299,0.000006976864,0.00005357565,0.9977448,0.0002591774,0.0008753708],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8920135,"threshold_uncertainty_score":0.3612506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02427368322174595,"score_gpt":0.2766527202934732,"score_spread":0.2523790370717273,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}