{"id":"W4231081785","doi":"10.1515/iupac.79.1233","title":"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; Computer science; Toxicology; Chemistry; Philosophy; Biology; 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":[0.002008542,0.001366683,0.001866422,0.00364531,0.0007643113,0.002470633,0.002621084,0.001784594,0.1272569],"category_scores_gemma":[0.01962161,0.0005704883,0.002204953,0.006643759,0.000292981,0.0019405,0.001666176,0.001894683,0.06717602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001726379,"about_ca_system_score_gemma":0.003913453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0255867,"about_ca_topic_score_gemma":0.03559151,"domain_scores_codex":[0.9969525,0.0005641175,0.0007920834,0.0009823702,0.0004432719,0.0002655899],"domain_scores_gemma":[0.9922806,0.002175126,0.00143026,0.001259014,0.002479859,0.000375186],"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":[0.0003027413,0.00003758422,0.01039128,0.004170334,0.0002344943,0.00006200872,0.00006109896,0.0002939125,0.00006823893,0.001620585,0.9612758,0.02148183],"study_design_scores_gemma":[0.0004453912,0.00004631421,0.02124647,0.003583775,0.0002958243,0.0002896199,0.0001777537,0.0002881374,0.0001602615,0.003437888,0.9699665,0.00006215165],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003890652,0.0008508583,0.0003326909,0.000269224,0.00009741019,0.0001044633,0.9933164,0.000142007,0.004497818],"genre_scores_gemma":[0.003087891,0.001588262,0.001544342,0.0007370614,0.0001183319,0.0007802379,0.986773,0.0001184362,0.005252462],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1272569,"threshold_uncertainty_score":0.4257167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02887827876444242,"score_gpt":0.4386239554031811,"score_spread":0.4097456766387387,"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."}}