{"id":"W4241114869","doi":"10.1515/iupac.79.2154","title":"Toxicovigilance","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Animal testing and alternatives","field":"Veterinary","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; 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":[0.002648976,0.001606296,0.001915947,0.005364069,0.0007178498,0.00309883,0.003205071,0.002230886,0.08499701],"category_scores_gemma":[0.02312655,0.000659001,0.002781675,0.008329974,0.0003507673,0.001839197,0.002174722,0.001904774,0.05926539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002328003,"about_ca_system_score_gemma":0.004249433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0187111,"about_ca_topic_score_gemma":0.03178792,"domain_scores_codex":[0.9967021,0.0006960919,0.0008649349,0.0008807359,0.0006404442,0.0002156258],"domain_scores_gemma":[0.9904965,0.004074934,0.001559027,0.001729062,0.001713106,0.0004273649],"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":[0.0002912449,0.00003200589,0.003474216,0.00593512,0.000295405,0.00007995687,0.0000478416,0.0009996578,0.0001884862,0.001580915,0.9745346,0.01254051],"study_design_scores_gemma":[0.0004084165,0.00003654424,0.005035426,0.002244184,0.0002686699,0.0001723667,0.00005062799,0.0006029975,0.0002913993,0.002721681,0.9881166,0.00005108448],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001186815,0.0003019987,0.0001411873,0.00009960958,0.00001982066,0.00002958821,0.9980758,0.000212677,0.001000487],"genre_scores_gemma":[0.0007079833,0.0003545397,0.0006413538,0.0002039955,0.00001409858,0.0001920748,0.9971212,0.00007572324,0.0006889665],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08499701,"threshold_uncertainty_score":0.2843433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09955456929824967,"score_gpt":0.5131250572506032,"score_spread":0.4135704879523535,"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."}}