{"id":"W2302607968","doi":"10.1093/mutage/gew009","title":"Empirical analysis of BMD metrics in genetic toxicology part II:<i>in vivo</i>potency comparisons to promote reductions in the use of experimental animals for genetic toxicity assessment","year":2016,"lang":"en","type":"article","venue":"Mutagenesis","topic":"Carcinogens and Genotoxicity Assessment","field":"Biochemistry, Genetics and Molecular Biology","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada","funders":"Health Canada; National Centre for the Replacement, Refinement and Reduction of Animals in Research; Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Covariate; Genotoxicity; In vivo; Toxicology; Micronucleus test; Biology; Pharmacology; Computational biology; Potency; Genetics; Statistics; Toxicity; Medicine; Internal medicine; Mathematics; In vitro","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004445465,0.0002083373,0.0005439981,0.0006226086,0.00005777796,0.00001297392,0.0002999618,0.000167674,0.00005328512],"category_scores_gemma":[0.0001207075,0.0001579744,0.0002605061,0.001406196,0.00009507064,0.000006161617,0.0001759031,0.00005724944,3.321516e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001264514,"about_ca_system_score_gemma":0.0001409781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002829558,"about_ca_topic_score_gemma":0.002636326,"domain_scores_codex":[0.9977929,0.0002756878,0.0007729252,0.0005401552,0.000242418,0.000375911],"domain_scores_gemma":[0.9989803,0.000117701,0.0001814698,0.0005499627,0.00009381846,0.00007678258],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009747976,0.001011184,0.1602516,0.00001188297,0.0001506749,0.000003906179,0.0002474621,0.003612555,0.8332673,0.00001498719,0.0004212027,0.00090976],"study_design_scores_gemma":[0.0006375013,0.001031399,0.4863044,0.00001357575,0.0001665735,0.000003644733,0.0002671238,0.0007678408,0.5070025,0.000006785416,0.003617336,0.0001813861],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9919249,0.0003771376,0.005873118,0.0004695988,0.00007130607,0.0009864328,0.000277345,0.000003374451,0.00001671962],"genre_scores_gemma":[0.9795972,0.0001029336,0.01964687,0.0001539631,0.00003936337,0.0003653774,0.00001628967,0.00001708805,0.00006092129],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3262649,"threshold_uncertainty_score":0.6442009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07693361354917311,"score_gpt":0.3619566600102259,"score_spread":0.2850230464610528,"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."}}