{"id":"W4255990237","doi":"10.1515/iupac.79.1223","title":"Environmental Medicine","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Chemical nomenclature; Hazard; Computer science; Multidisciplinary approach; Toxicology; Chemistry; Biology; Philosophy; Political science; Linguistics; Law","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":[0.001217755,0.001119141,0.001260426,0.003393271,0.000742563,0.002900661,0.001844024,0.001381721,0.184966],"category_scores_gemma":[0.0122013,0.0004180936,0.001556056,0.005692626,0.0002733261,0.001841622,0.001927458,0.001305148,0.1355904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001468432,"about_ca_system_score_gemma":0.003374886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01552254,"about_ca_topic_score_gemma":0.02847122,"domain_scores_codex":[0.9985276,0.0002743845,0.0002719616,0.0004702735,0.0003020196,0.0001537184],"domain_scores_gemma":[0.9956042,0.001356683,0.0005747775,0.0009247463,0.001192761,0.000346909],"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":[0.0001196781,0.00001654055,0.002534286,0.00196623,0.00007427433,0.00003172176,0.0000261372,0.0002026944,0.00007253931,0.001285325,0.9736279,0.02004268],"study_design_scores_gemma":[0.00008562511,0.00001042394,0.003805572,0.000883153,0.00004554963,0.00006911981,0.00004780038,0.00009980115,0.00008827879,0.001465321,0.9933844,0.00001493113],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001551625,0.000487592,0.0001584686,0.0002271838,0.00008274669,0.00002450141,0.9937562,0.0002011877,0.00490692],"genre_scores_gemma":[0.001075234,0.0006956337,0.0006064647,0.0004657014,0.00004739091,0.0001031355,0.9933548,0.00007947147,0.00357222],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.184966,"threshold_uncertainty_score":0.6187727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01092428339754403,"score_gpt":0.3678046659398646,"score_spread":0.3568803825423206,"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."}}