{"id":"W3203933639","doi":"10.1016/j.comtox.2021.100191","title":"In silico approaches in carcinogenicity hazard assessment: Current status and future needs","year":2021,"lang":"en","type":"article","venue":"Computational Toxicology","topic":"Carcinogens and Genotoxicity Assessment","field":"Biochemistry, Genetics and Molecular Biology","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"Government of Canada; Health Canada","funders":"National Institute of Environmental Health Sciences; National Institutes of Health","keywords":"In silico; Scope (computer science); Protocol (science); Computer science; Hazard; Risk analysis (engineering); Computational biology; Biology; Business; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00677463,0.001470428,0.002928085,0.001145696,0.0004208774,0.004765187,0.004662205,0.001920787,0.005574649],"category_scores_gemma":[0.01238332,0.0007079212,0.001535776,0.001162485,0.001486666,0.003413636,0.002098509,0.002660193,0.001434565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001057526,"about_ca_system_score_gemma":0.002450686,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005929107,"about_ca_topic_score_gemma":0.006188584,"domain_scores_codex":[0.9983353,0.001008905,0.00007783158,0.0001710158,0.0003458197,0.00006112269],"domain_scores_gemma":[0.9841288,0.01359403,0.0003424294,0.00069998,0.0009273192,0.0003074767],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003469861,0.001130994,0.01068085,0.005500334,0.00163,0.0001425618,0.0002813053,0.6278289,0.004800101,0.07112852,0.007064003,0.2694653],"study_design_scores_gemma":[0.0001107309,0.0002283384,0.001349814,0.0007409883,0.0004041407,0.0001186521,0.0003345121,0.8036752,0.002017755,0.1584018,0.03254315,0.00007491517],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.04581078,0.05188193,0.8703489,0.01160623,0.0004858338,0.000187822,0.001440092,0.002620632,0.01561779],"genre_scores_gemma":[0.3517924,0.09011433,0.5461955,0.003316211,0.000863835,0.0006858896,0.002887449,0.0006490572,0.003495467],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.00677463,"threshold_uncertainty_score":0.03582811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02769727882072802,"score_gpt":0.3026332889388217,"score_spread":0.2749360101180937,"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."}}