{"id":"W2946997574","doi":"10.1016/j.cotox.2019.02.005","title":"Toxicogenomic applications in risk assessment at Health Canada","year":2019,"lang":"en","type":"article","venue":"Current Opinion in Toxicology","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Public Health Agency of Canada; Wilfrid Laurier University; Health Canada","funders":"Health Canada","keywords":"Toxicogenomics; Risk assessment; Risk analysis (engineering); Health risk assessment; Data science; Computer science; Biology; Business; Computer security; Genetics; Gene","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002533053,0.0001412612,0.0002637967,0.00009962224,0.00006033437,0.000005604822,0.000169084,0.00007532888,0.00006433773],"category_scores_gemma":[0.00002416706,0.0001422,0.00003971135,0.0001565237,0.00002940962,0.000002037053,0.0002086666,0.000174479,0.000008929446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004184948,"about_ca_system_score_gemma":0.0005613054,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.007867528,"about_ca_topic_score_gemma":0.1879188,"domain_scores_codex":[0.9986874,0.0001299857,0.0003349429,0.0004165978,0.00008629802,0.0003447661],"domain_scores_gemma":[0.9994248,0.00002988311,0.0001591318,0.0002942825,0.00002183162,0.00007012195],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004048838,0.0003415,0.9447833,0.000132773,0.00003894888,2.397475e-7,0.00005211307,0.0004075945,0.03006854,0.003284226,0.01519235,0.00565787],"study_design_scores_gemma":[0.0009191892,0.0002094593,0.340212,0.00001336121,0.000002249939,0.000002304476,0.00009586113,0.00008591841,0.001225305,0.000151802,0.6568863,0.0001961791],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.986249,0.008941999,0.0002192127,0.0006555339,0.0025557,0.0007283524,0.00009483058,0.000004847619,0.0005505761],"genre_scores_gemma":[0.9901659,0.00872289,0.000204354,0.0001103084,0.0001606086,0.0001924865,0.0002940231,0.00001353448,0.0001358539],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.641694,"threshold_uncertainty_score":0.9987392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01712355598420261,"score_gpt":0.3276985836524229,"score_spread":0.3105750276682203,"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."}}