{"id":"W4239078170","doi":"10.1515/iupac.81.0665","title":"Per Capita Death Rate","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Health and Conflict Studies","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Ecotoxicology; Relation (database); Per capita; Environmental risk assessment; Environmental science; Ecology; Computer science; Risk assessment; Environmental health; Biology; Data mining; Medicine; Philosophy; Linguistics","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":[0.001267946,0.001200288,0.00155284,0.005014943,0.0004330072,0.00239603,0.002047952,0.001141683,0.05806341],"category_scores_gemma":[0.01049495,0.0004672793,0.001734592,0.007728656,0.0003251229,0.001337748,0.001274121,0.002418234,0.05727449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001894468,"about_ca_system_score_gemma":0.001388495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02703788,"about_ca_topic_score_gemma":0.02262776,"domain_scores_codex":[0.9982323,0.0002486267,0.0003441484,0.0005687953,0.0004137253,0.0001924273],"domain_scores_gemma":[0.9959407,0.001046665,0.001043521,0.0004735642,0.001272887,0.0002227524],"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":[0.0001462482,0.00003270027,0.01781219,0.001140434,0.0001671866,0.00004407013,0.0000492228,0.001141272,0.00006784066,0.001842011,0.9693975,0.008159315],"study_design_scores_gemma":[0.0004621817,0.00005318311,0.05809416,0.001034338,0.0001817471,0.0004732541,0.0002391655,0.001958168,0.0003414766,0.002517668,0.934557,0.00008756555],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0007692527,0.0002743489,0.0001035928,0.0001229692,0.00005842217,0.0000160959,0.9965833,0.0001167684,0.001955218],"genre_scores_gemma":[0.003825886,0.0005044026,0.0002760181,0.0001468552,0.00005683318,0.0001293799,0.9924105,0.00006508621,0.002584967],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05806341,"threshold_uncertainty_score":0.1942415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06587188465853022,"score_gpt":0.5459116002549855,"score_spread":0.4800397155964553,"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."}}