{"id":"W4246709373","doi":"10.1515/iupac.79.1323","title":"Genetic Epidemiology","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Multidisciplinary approach; Computer science; Hazard; Toxicology; Biology; Chemistry; Philosophy; 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":[0.001563195,0.001178265,0.001608452,0.00396574,0.0006216283,0.001941748,0.002006841,0.00159851,0.09466768],"category_scores_gemma":[0.01943033,0.0005776004,0.001802574,0.007368967,0.0002293814,0.001273151,0.001459864,0.0016039,0.03848101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001225694,"about_ca_system_score_gemma":0.002709168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02108129,"about_ca_topic_score_gemma":0.03177216,"domain_scores_codex":[0.9980002,0.000391745,0.0004755213,0.0006825174,0.0002934964,0.0001565496],"domain_scores_gemma":[0.9932237,0.002504452,0.001072002,0.001264043,0.001610327,0.0003254903],"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":[0.0002832365,0.0000319622,0.01417226,0.003737428,0.0003751104,0.00008123642,0.00005424947,0.0004053654,0.0001043346,0.001711435,0.960482,0.01856133],"study_design_scores_gemma":[0.0006149752,0.00004625348,0.03812427,0.003597712,0.0004415291,0.0004510885,0.0001400606,0.0004210104,0.0002263401,0.003966956,0.9519026,0.00006726287],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003727745,0.0004831334,0.0002613166,0.0001305405,0.00004831636,0.00004100208,0.9966707,0.00009719943,0.001895193],"genre_scores_gemma":[0.002561866,0.000910671,0.001114136,0.000334613,0.00005138038,0.0003704465,0.9924452,0.00006712267,0.002144696],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09466768,"threshold_uncertainty_score":0.3166949,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02518350084013138,"score_gpt":0.4212044419011129,"score_spread":0.3960209410609815,"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."}}