{"id":"W4238079926","doi":"10.1515/iupac.79.1647","title":"Mortality","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Global Health Care Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Computer science; Hazard; Multidisciplinary approach; Toxicology; Chemistry; Philosophy; Biology; Linguistics; Sociology; Social science","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","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002222725,0.0006304877,0.001233395,0.0002124236,0.0006974434,0.00001388968,0.0007860151,0.001429794,0.02262314],"category_scores_gemma":[0.002303304,0.0004605358,0.0002146176,0.0002653274,0.0001911891,0.0001057623,0.0005200994,0.002021182,0.0002459633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002348086,"about_ca_system_score_gemma":0.004939871,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003443787,"about_ca_topic_score_gemma":0.01834759,"domain_scores_codex":[0.9933369,0.0009405082,0.001455434,0.0008296981,0.001992665,0.001444759],"domain_scores_gemma":[0.9943659,0.000600546,0.0008393,0.001964781,0.001633309,0.0005961223],"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":[0.0001156605,0.0001048794,0.0003178805,0.001290819,0.00008206905,0.00008162456,0.00003982772,6.188287e-8,4.707972e-7,0.00003957432,0.9975217,0.0004054267],"study_design_scores_gemma":[0.00103024,0.0001509935,0.001533758,0.002334551,0.0001317991,0.000002381371,0.0001450194,3.823016e-7,5.321445e-7,0.0004577871,0.9937435,0.0004689975],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003976538,0.001383667,0.00002393298,0.0020243,0.006564221,0.001392637,0.9871384,0.0002659156,0.0008092726],"genre_scores_gemma":[0.00002732597,0.001848607,0.00003103121,0.003158884,0.004308183,0.00009883225,0.9884878,0.00006935943,0.001969975],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02237718,"threshold_uncertainty_score":0.9998665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06800352030987143,"score_gpt":0.5986578110108081,"score_spread":0.5306542907009366,"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."}}