{"id":"W4239132362","doi":"10.1515/iupac.76.0115","title":"Adverse Effect","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Chemical Safety and Risk Management","field":"Chemical Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Toxicokinetics; Hazard; Relation (database); Multidisciplinary approach; Computer science; Toxicology; Medicine; Pharmacology; Chemistry; Data mining; Political science; Biology; Philosophy; Law; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003665296,0.0005407775,0.0006930644,0.000106169,0.00006497416,0.00001527594,0.0005549745,0.0004873078,0.006473003],"category_scores_gemma":[0.0005688349,0.0003650877,0.0003437607,0.0001618408,0.00008785892,0.00006207727,0.0003751174,0.0006760223,0.00002833718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005993089,"about_ca_system_score_gemma":0.00008027156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007259433,"about_ca_topic_score_gemma":0.00005397405,"domain_scores_codex":[0.9974774,0.00003954113,0.0004552378,0.0005539576,0.0009310327,0.0005428731],"domain_scores_gemma":[0.9984189,0.0002288309,0.0001524145,0.0008626217,0.0001040093,0.000233264],"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":[0.0002057064,0.0000926015,0.00000117047,0.0004951308,0.0001787389,0.00007913181,0.000002042013,0.0000236659,0.0002994076,0.00001431603,0.9940357,0.004572392],"study_design_scores_gemma":[0.001313591,0.0001046218,0.000002445866,0.0005974089,0.0002097496,0.000004221107,0.000002130922,0.00005045037,0.0009159178,0.00004001991,0.9962386,0.000520828],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00006480375,0.0003841783,0.0005154076,0.0002974654,0.0006679565,0.0002960757,0.9973498,0.0002013945,0.0002228972],"genre_scores_gemma":[0.00003245204,0.0008145472,0.00002609622,0.000146334,0.001260967,0.00002403394,0.9964218,0.0000539482,0.001219826],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.006444666,"threshold_uncertainty_score":0.9998801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006156513486906838,"score_gpt":0.3408373507250299,"score_spread":0.3346808372381231,"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."}}