{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001431172,0.00146483,0.001389325,0.003146871,0.000713727,0.002599388,0.002371104,0.001575496,0.1479639],"category_scores_gemma":[0.01168829,0.000457237,0.001748159,0.005524516,0.0002543612,0.001665521,0.001513892,0.001751807,0.1581461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001428832,"about_ca_system_score_gemma":0.002399155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02075841,"about_ca_topic_score_gemma":0.0299383,"domain_scores_codex":[0.9979631,0.0003422031,0.0003786717,0.0006564694,0.0004386359,0.0002209671],"domain_scores_gemma":[0.9956125,0.001014454,0.0006137818,0.0008194398,0.001657266,0.0002826466],"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":[0.0001211608,0.00002038526,0.00320141,0.0006319712,0.00005046236,0.00001633655,0.00001843809,0.0001320668,0.0000348651,0.0005029749,0.9882768,0.00699307],"study_design_scores_gemma":[0.00031794,0.00003368632,0.01228256,0.0007363425,0.00008992531,0.0001099944,0.0001140942,0.000305028,0.0001721823,0.001620861,0.9841765,0.00004094652],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001716247,0.0001110903,0.00007491284,0.0001133567,0.00004829191,0.00002239362,0.9975581,0.0001607874,0.001739423],"genre_scores_gemma":[0.0007654598,0.0001453232,0.0002756218,0.0001935771,0.00003380677,0.0001630548,0.9958438,0.00006084794,0.002518412],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1479639,"threshold_uncertainty_score":0,"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."}}