{"id":"W4234627407","doi":"10.1515/iupac.88.0805","title":"Fibroblast","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Cancer Diagnosis and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; Linguistics; Philosophy; Data mining","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001485796,0.0004107835,0.0008605225,0.0001395899,0.0001599922,0.00008376173,0.0002225933,0.000309212,0.004592145],"category_scores_gemma":[0.0002521328,0.0003229694,0.0003075366,0.00005464141,0.0001319615,0.00004434424,0.0001317146,0.0004343012,0.0000137211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007042256,"about_ca_system_score_gemma":0.001244161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006585564,"about_ca_topic_score_gemma":0.001840965,"domain_scores_codex":[0.9979208,0.00001791477,0.0003201476,0.0004951678,0.0009026853,0.0003433102],"domain_scores_gemma":[0.9975821,0.00004148951,0.0002685447,0.00151967,0.0003201572,0.000268086],"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":[0.0002910183,0.0007165009,0.0000953592,0.0003798206,0.0003552951,0.0006062685,0.000004956672,4.403281e-7,0.000001453007,0.000001343365,0.9937956,0.003751948],"study_design_scores_gemma":[0.002485528,0.0008709097,0.001141184,0.002641442,0.0006058991,0.00008619458,0.00000661888,0.000001327122,0.00002773053,0.00001556061,0.9918484,0.000269207],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001518228,0.001563082,0.000002950641,0.001930075,0.0004046971,0.0004831829,0.9952295,0.0000461624,0.000188511],"genre_scores_gemma":[0.0000558312,0.00225564,0.0000641072,0.000430902,0.001476945,0.000045686,0.9945195,0.00004132107,0.001110024],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.004578424,"threshold_uncertainty_score":0.9999222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0216375185753424,"score_gpt":0.462258596732717,"score_spread":0.4406210781573746,"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."}}