{"id":"W2194873522","doi":"10.1124/jpet.115.228239","title":"Adverse Outcome Pathways—Organizing Toxicological Information to Improve Decision Making","year":2015,"lang":"en","type":"review","venue":"Journal of Pharmacology and Experimental Therapeutics","topic":"Animal testing and alternatives","field":"Veterinary","cited_by":196,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"National Academy of Sciences; U.S. Environmental Protection Agency","keywords":"Adverse Outcome Pathway; ADME; Context (archaeology); Risk analysis (engineering); Test strategy; Computer science; Biochemical engineering; Pharmacology; Computational biology; Business; Drug; Biology; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0006648081,0.0003449044,0.001039599,0.0002431329,0.0001256245,0.00004431313,0.0003207399,0.0002590038,0.0001255972],"category_scores_gemma":[0.00004475625,0.0002452115,0.0002363248,0.0001368106,0.00007473912,0.0003617816,0.0002621928,0.0006516675,0.00006860026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003221448,"about_ca_system_score_gemma":0.0001464446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.225001e-7,"about_ca_topic_score_gemma":2.783022e-8,"domain_scores_codex":[0.9979873,0.0002276838,0.001106785,0.0001687171,0.0002508917,0.0002586472],"domain_scores_gemma":[0.9983236,0.0003092512,0.0009998737,0.0000797996,0.0001422035,0.0001452235],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001214425,0.0002772122,0.00002502399,0.0005541394,0.0004722036,0.0003049351,0.001672211,0.000003773442,0.007526059,0.00006387796,0.0007819114,0.9871042],"study_design_scores_gemma":[0.001098971,0.005445372,0.00001040992,0.001178085,0.0006161463,0.001890885,0.0009266664,0.00004677709,0.0004444503,0.00009623002,0.987848,0.0003980048],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.03790369,0.9588588,0.0003012391,0.0000299809,0.002138123,0.0004162666,0.00002565502,0.00003492432,0.0002913277],"genre_scores_gemma":[0.1682109,0.820855,0.006913193,0.002668955,0.001216707,0.00002697118,0.000006251295,0.00006263548,0.00003942021],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9870661,"threshold_uncertainty_score":0.9999435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.352781874473634,"score_gpt":0.5302013049341451,"score_spread":0.1774194304605111,"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."}}