{"id":"W4233386230","doi":"10.1515/iupac.79.1498","title":"Interspecies Dose Conversion","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; Toxicology; Hazard; Computer science; Multidisciplinary approach; Chemistry; Biology; Philosophy; Political science; Linguistics; 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":[0.004089716,0.002277109,0.002560174,0.004845106,0.0006688983,0.003219987,0.003705365,0.001968312,0.08867474],"category_scores_gemma":[0.02467503,0.0008400445,0.0049712,0.006129621,0.0004960676,0.00205383,0.002229412,0.002848039,0.06635362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00217272,"about_ca_system_score_gemma":0.002696728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01225968,"about_ca_topic_score_gemma":0.01731358,"domain_scores_codex":[0.9941108,0.00106046,0.00128297,0.002061558,0.001166146,0.0003181539],"domain_scores_gemma":[0.9917098,0.002827219,0.0009629296,0.002480658,0.001844441,0.0001749873],"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":[0.0009884271,0.0001480094,0.006210412,0.005839185,0.0008985889,0.00006464234,0.00004377416,0.002634948,0.0005580045,0.001957797,0.9417918,0.03886443],"study_design_scores_gemma":[0.0008467099,0.0001133834,0.009969062,0.001061322,0.0004175766,0.0002065013,0.00005886623,0.001075433,0.001219466,0.003903269,0.9810372,0.00009118894],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003659094,0.0004744393,0.0004749619,0.00008419302,0.0001054535,0.0001113785,0.9961415,0.0005065833,0.001735636],"genre_scores_gemma":[0.002798855,0.0005066813,0.002188751,0.0003093114,0.00005482414,0.0007700584,0.9897574,0.0003140406,0.003299973],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08867474,"threshold_uncertainty_score":0.2966465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01396955395743049,"score_gpt":0.3764058119153942,"score_spread":0.3624362579579637,"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."}}