{"id":"W4413363812","doi":"10.1016/j.comtox.2025.100374","title":"Conservative consensus QSAR approach for the prediction of rat acute oral toxicity","year":2025,"lang":"en","type":"article","venue":"Computational Toxicology","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Quantitative structure–activity relationship; Toxicity; Acute toxicity; Computer science; Artificial intelligence; Machine learning; Computational biology; Pharmacology; Medicine; Biology; Internal medicine","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":[0.0007562135,0.0001626953,0.0002993082,0.0001730934,0.0002568142,0.00005058306,0.0007082897,0.0001020922,0.000005790406],"category_scores_gemma":[0.0003969738,0.0001343595,0.0001369243,0.0006567047,0.0003649771,0.0001322662,0.0002828549,0.0001502163,0.000002039744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009499626,"about_ca_system_score_gemma":0.0006249179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005884702,"about_ca_topic_score_gemma":0.000002670061,"domain_scores_codex":[0.9982131,0.0004184505,0.0004697901,0.000427131,0.0002450849,0.0002264195],"domain_scores_gemma":[0.9925984,0.006306223,0.0002118807,0.000283896,0.0005583325,0.00004130189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008492253,0.0001603262,0.0002957949,0.00002683568,0.0002421502,0.000001206338,0.0001607801,0.5411614,0.0004366813,0.4438081,0.00830386,0.00531796],"study_design_scores_gemma":[0.0008199657,0.0001420535,0.01239152,0.000007247406,0.00004584221,0.00001814854,0.00003708961,0.8642454,0.001192169,0.1197041,0.001311262,0.00008523511],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0200224,0.0001013686,0.9723808,0.00455027,0.001106665,0.0007873826,0.00008613714,0.00007826525,0.0008866843],"genre_scores_gemma":[0.4851678,0.000002679132,0.5125552,0.001710176,0.00004681349,0.0001453654,0.00006301596,0.000006881154,0.0003021392],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4651454,"threshold_uncertainty_score":0.547902,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05445501392409084,"score_gpt":0.3457392722519085,"score_spread":0.2912842583278177,"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."}}