{"id":"W4255602460","doi":"10.1515/iupac.76.0419","title":"Toxicology","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; Toxicokinetics; Relation (database); Toxicology; Computer science; Medicine; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003673888,0.0004108523,0.0005727773,0.0001589892,0.0001135095,0.00003744808,0.0005364436,0.0003393623,0.007778796],"category_scores_gemma":[0.0009244568,0.0002981553,0.0001555238,0.00009209698,0.0002045885,0.00006451194,0.0002889155,0.0004997265,0.00002704794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002516617,"about_ca_system_score_gemma":0.0003470043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009154968,"about_ca_topic_score_gemma":0.0001154055,"domain_scores_codex":[0.9978664,0.0001453285,0.0003970257,0.0005646509,0.000570551,0.0004560655],"domain_scores_gemma":[0.9984199,0.0002670853,0.0002859325,0.0006290101,0.000259293,0.0001387339],"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":[0.0004721753,0.0001753483,0.00001141157,0.00007676527,0.00009315452,0.0007092275,0.000007734839,7.495179e-8,0.0001136856,0.00001983303,0.9948969,0.00342363],"study_design_scores_gemma":[0.0005493254,0.002186218,0.00007787547,0.0003520659,0.00005613281,0.0001769067,0.00001480476,0.000002665962,0.000009444595,0.0002982809,0.9958844,0.0003919236],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001564446,0.0004153936,0.00007130276,0.0003519049,0.0008585451,0.0001572071,0.9960468,0.00016697,0.0003673796],"genre_scores_gemma":[0.0003140034,0.0002676911,0.00009730004,0.0003225675,0.001970585,0.00001392461,0.9956218,0.00004690924,0.001345198],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.007751748,"threshold_uncertainty_score":0.9999471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1036462976646196,"score_gpt":0.5157586889485893,"score_spread":0.4121123912839698,"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."}}