{"id":"W4235118998","doi":"10.1515/iupac.76.0218","title":"Elimination Rate","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Historical and Scientific Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Toxicokinetics; Hazard; Relation (database); Computer science; Toxicology; Medicine; Chemistry; Pharmacology; Data mining; Biology; Philosophy; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001432509,0.001320442,0.00142099,0.00302154,0.0004489089,0.002260097,0.002055801,0.001108227,0.09522118],"category_scores_gemma":[0.0136596,0.0004157979,0.002146751,0.004479881,0.0002111907,0.00173256,0.0009862318,0.001672338,0.108986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001283263,"about_ca_system_score_gemma":0.001646435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01456397,"about_ca_topic_score_gemma":0.01701549,"domain_scores_codex":[0.9983141,0.0002757979,0.0003277115,0.0006533328,0.0003024764,0.0001264983],"domain_scores_gemma":[0.9958644,0.001414212,0.000598822,0.0008466205,0.001092052,0.0001839063],"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":[0.0002565617,0.00004645247,0.006214904,0.001332763,0.0001455868,0.00003178192,0.0000301151,0.0006449167,0.00008704624,0.0010545,0.9739221,0.0162333],"study_design_scores_gemma":[0.0003821773,0.0000557313,0.0132629,0.0007696357,0.0001572294,0.000178509,0.00008792249,0.0008855509,0.0003044113,0.002614174,0.9812487,0.00005301431],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004144553,0.0002411197,0.0001915891,0.00009287512,0.00004702725,0.00002611392,0.9970901,0.0002789131,0.001617762],"genre_scores_gemma":[0.001515198,0.0002507928,0.0006132263,0.0001414415,0.00003270822,0.0001814117,0.9946535,0.0001453932,0.002466299],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09522118,"threshold_uncertainty_score":0.3185466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02717610733615124,"score_gpt":0.405824009370164,"score_spread":0.3786479020340128,"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."}}