{"id":"W4236033580","doi":"10.1515/iupac.79.2126","title":"Tolerable Risk","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; Hazard; Computer science; Multidisciplinary approach; Toxicology; Chemistry; Philosophy; Biology; Linguistics; Political science; Law; Organic chemistry","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":[0.00201801,0.001496224,0.001544476,0.004204865,0.0005102988,0.003012677,0.002534802,0.001603267,0.1095317],"category_scores_gemma":[0.02004202,0.0004955432,0.002890742,0.004959983,0.0003327378,0.002506973,0.001420277,0.002295301,0.06303032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001787564,"about_ca_system_score_gemma":0.002314961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01107331,"about_ca_topic_score_gemma":0.01544264,"domain_scores_codex":[0.9971778,0.0004842587,0.0005586252,0.000824742,0.0007765683,0.0001779559],"domain_scores_gemma":[0.9933482,0.003037059,0.0008696071,0.001240134,0.001264623,0.0002403404],"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":[0.0002342536,0.00005225633,0.005646642,0.002807166,0.0002951935,0.00004287785,0.00002907294,0.002902599,0.0001059876,0.004283566,0.9499453,0.03365511],"study_design_scores_gemma":[0.0003201228,0.00005392992,0.007560429,0.001204028,0.0001767549,0.0002106606,0.00007040927,0.0016872,0.0001902723,0.0116464,0.9768298,0.00004993884],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003353102,0.0006191768,0.000576791,0.0002149994,0.00006957146,0.0000448613,0.993091,0.0003253767,0.004722877],"genre_scores_gemma":[0.004120199,0.0009233067,0.002000839,0.0004787403,0.00007547242,0.0002381462,0.9890171,0.0001592512,0.002986882],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1095317,"threshold_uncertainty_score":0.36642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01045863452434527,"score_gpt":0.372504353530226,"score_spread":0.3620457190058807,"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."}}