{"id":"W2303509185","doi":"10.1093/mutage/gew011","title":"Genetic toxicology at the crossroads—from qualitative hazard evaluation to quantitative risk assessment","year":2016,"lang":"en","type":"article","venue":"Mutagenesis","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Health Canada; National Centre for the Replacement, Refinement and Reduction of Animals in Research","keywords":"Risk assessment; Hazard; Hazard analysis; Risk analysis (engineering); Computer science; Data science; Computational biology; Toxicology; Medicine; Biology; Engineering; Reliability engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.09497812,0.001743791,0.002716795,0.005109864,0.003361003,0.02062659,0.005740694,0.007738551,0.009342892],"category_scores_gemma":[0.07549169,0.001207733,0.001999989,0.003659758,0.02087778,0.0187591,0.01256585,0.01723911,0.003154407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01044059,"about_ca_system_score_gemma":0.01025337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002901521,"about_ca_topic_score_gemma":0.002179378,"domain_scores_codex":[0.9225253,0.04851872,0.002053342,0.003875143,0.02163909,0.001388353],"domain_scores_gemma":[0.8682865,0.09719268,0.004733342,0.006029048,0.02038416,0.003374293],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001402304,0.0002704789,0.001750616,0.003995453,0.0002362074,0.0005398338,0.01043771,0.005679698,0.004417005,0.531271,0.1375668,0.3036949],"study_design_scores_gemma":[0.00002020854,0.0002137818,0.0008720495,0.0032477,0.0000493833,0.0002508881,0.006269692,0.003520129,0.002617302,0.5641472,0.4186403,0.0001513032],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007866124,0.07131731,0.4184761,0.4085549,0.0305278,0.0007965108,0.0004898095,0.0008760586,0.06109532],"genre_scores_gemma":[0.2001337,0.1215775,0.4405653,0.1399004,0.03530411,0.002093563,0.0009228211,0.002712535,0.05679],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.09497812,"threshold_uncertainty_score":0.5022984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03300443535885134,"score_gpt":0.4016892001723688,"score_spread":0.3686847648135175,"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."}}