{"id":"W2979332126","doi":"10.3389/fdata.2019.00036","title":"TGx-DDI, a Transcriptomic Biomarker for Genotoxicity Hazard Assessment of Pharmaceuticals and Environmental Chemicals","year":2019,"lang":"en","type":"review","venue":"Frontiers in Big Data","topic":"Carcinogens and Genotoxicity Assessment","field":"Biochemistry, Genetics and Molecular Biology","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada","funders":"National Institute of Environmental Health Sciences","keywords":"Genotoxicity; Biomarker; Drug development; DNA damage; Biology; Drug; Computational biology; Pharmacology; Medicine; Toxicity; Genetics; DNA","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":[0.001899327,0.0008317897,0.0007337763,0.001549187,0.0003317306,0.001320453,0.0005342537,0.001219022,0.001074435],"category_scores_gemma":[0.001392305,0.0003817794,0.0007671757,0.001067543,0.0007661851,0.00107582,0.0008410849,0.001302585,0.0008207979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009211685,"about_ca_system_score_gemma":0.001072012,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007990817,"about_ca_topic_score_gemma":0.001493377,"domain_scores_codex":[0.9987544,0.0001817576,0.00008994631,0.0003607187,0.0005267021,0.00008646424],"domain_scores_gemma":[0.9990533,0.000334135,0.0002235176,0.00007723088,0.0002512542,0.00006047924],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008490838,0.00004041127,0.003302921,0.001315583,0.0000543902,0.0001599463,0.0001313147,0.0008642281,0.9160706,0.002151948,0.001341197,0.07448253],"study_design_scores_gemma":[0.000008414343,0.0005538042,0.01015803,0.0002754244,0.0001399497,0.001271669,0.0001459814,0.003620429,0.875286,0.00178994,0.1066435,0.0001068613],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.2439849,0.284272,0.4242007,0.005358072,0.002029429,0.001110437,0.01327455,0.002598724,0.02317105],"genre_scores_gemma":[0.4632407,0.1912079,0.3078791,0.004188899,0.0007744122,0.001115246,0.01119381,0.0004750668,0.01992505],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.001899327,"threshold_uncertainty_score":0.01004475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1653611024975338,"score_gpt":0.3996789004179755,"score_spread":0.2343177979204417,"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."}}