{"id":"W4248108777","doi":"10.1515/iupac.79.0931","title":"Biomarker of Effect","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Carcinogens and Genotoxicity Assessment","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Hazard; Computer science; Multidisciplinary approach; Toxicology; Data science; Chemistry; Biology; Philosophy; Political science; Linguistics; Law","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":[],"consensus_categories":[],"category_scores_codex":[0.002487964,0.001559753,0.001948679,0.003050386,0.000510166,0.002192428,0.00204155,0.001534375,0.09257286],"category_scores_gemma":[0.02500178,0.0003782978,0.003174805,0.003239909,0.0003926471,0.001719854,0.001330495,0.001828056,0.03513379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001359914,"about_ca_system_score_gemma":0.002638286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006694297,"about_ca_topic_score_gemma":0.01302277,"domain_scores_codex":[0.9971541,0.0004578932,0.0006657409,0.001031103,0.0005036277,0.0001873973],"domain_scores_gemma":[0.9907471,0.003912657,0.001648991,0.001554595,0.00181267,0.0003240028],"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":[0.002196947,0.0001563391,0.04322444,0.01616383,0.001931836,0.00011675,0.00009651108,0.001576494,0.0006866814,0.004181029,0.8372812,0.09238795],"study_design_scores_gemma":[0.0008237323,0.0002618214,0.05032683,0.003487778,0.001979487,0.000439148,0.00009915638,0.0006424797,0.0009314983,0.008584765,0.9323218,0.0001014596],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001195671,0.002384195,0.0007345655,0.0002868343,0.0002212952,0.0001543567,0.989639,0.0002688489,0.005115272],"genre_scores_gemma":[0.01413762,0.002475885,0.003434859,0.001377771,0.0002206557,0.001053311,0.9698047,0.0001891929,0.007305997],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09257286,"threshold_uncertainty_score":0.3096871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008999754807790037,"score_gpt":0.3891677346084857,"score_spread":0.3801679798006957,"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."}}