{"id":"W4220678256","doi":"10.1016/j.yrtph.2022.105143","title":"R-ODAF: Omics data analysis framework for regulatory application","year":2022,"lang":"en","type":"article","venue":"Regulatory Toxicology and Pharmacology","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Health Canada","funders":"Imperial College London; European Chemical Industry Council","keywords":"Workflow; Computer science; Toxicogenomics; Raw data; Pipeline (software); Data mining; False positive paradox; Credibility; Data science; Database; Biology; Machine learning","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":[0.02550277,0.003332604,0.001829374,0.005017464,0.001404673,0.006635374,0.005996844,0.002678838,0.009649342],"category_scores_gemma":[0.02958437,0.00165032,0.005270516,0.003416683,0.00166389,0.003527149,0.005640697,0.004811289,0.008438159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001826438,"about_ca_system_score_gemma":0.00746697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006187803,"about_ca_topic_score_gemma":0.004589873,"domain_scores_codex":[0.9898767,0.003651488,0.001750256,0.001353159,0.002861031,0.0005073472],"domain_scores_gemma":[0.984499,0.007216946,0.001289077,0.003482045,0.002892556,0.0006202294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001110433,0.0004382462,0.004463034,0.006341771,0.0009669428,0.002273293,0.002233342,0.06771396,0.03536968,0.3038111,0.1943182,0.38096],"study_design_scores_gemma":[0.0003349829,0.0002228073,0.002045351,0.001161871,0.0002325411,0.001062052,0.0003721551,0.2349118,0.02684903,0.1745868,0.5578163,0.0004043556],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003347606,0.0001341715,0.953491,0.0004309148,0.00007397959,0.0003601355,0.003991811,0.04033908,0.0008441691],"genre_scores_gemma":[0.007321164,0.0003328923,0.9747896,0.0004949449,0.00007939764,0.001207819,0.01000652,0.004976323,0.000791306],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02550277,"threshold_uncertainty_score":0.1348732,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02322340327029346,"score_gpt":0.3256771253069512,"score_spread":0.3024537220366578,"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."}}