{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001918776,0.0006394938,0.00120844,0.000244068,0.001228284,0.00001523873,0.0005415407,0.0009327818,0.02595941],"category_scores_gemma":[0.001231685,0.0004308544,0.0001899865,0.0000976568,0.0001336135,0.00008131059,0.0004672036,0.001856724,0.000357645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009567771,"about_ca_system_score_gemma":0.005238327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001457946,"about_ca_topic_score_gemma":0.0022027,"domain_scores_codex":[0.9949436,0.0006856456,0.001180571,0.00071623,0.0009304714,0.001543463],"domain_scores_gemma":[0.9956124,0.0008228438,0.0005734892,0.001209794,0.001199327,0.0005821245],"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":[0.0002131836,0.00007838022,0.0001208512,0.0009163065,0.0001149315,0.00003950464,0.0005164439,3.623458e-8,0.000001635825,0.00004483579,0.9968314,0.001122496],"study_design_scores_gemma":[0.001538215,0.0001849466,0.0005830004,0.0009545755,0.0001199596,0.000001825353,0.0003261165,4.93245e-7,5.011521e-7,0.00008296457,0.9957238,0.000483599],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001490778,0.002606308,0.00004655949,0.01783707,0.003170201,0.00114439,0.9742265,0.0001494436,0.0006704469],"genre_scores_gemma":[0.000007841734,0.00675995,0.00001986525,0.01516825,0.003937012,0.0002335013,0.9637592,0.00007247765,0.0100419],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02560176,"threshold_uncertainty_score":0.9998143,"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."}}