{"id":"W2752299790","doi":"10.1038/ng.3947","title":"A functional genomics predictive network model identifies regulators of inflammatory bowel disease","year":2017,"lang":"en","type":"article","venue":"Nature Genetics","topic":"Inflammatory Bowel Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":271,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"National Institute of Allergy and Infectious Diseases; National Human Genome Research Institute; National Institute of Mental Health; National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; National Institute on Aging; National Institutes of Health","keywords":"Inflammatory bowel disease; Genome-wide association study; Biology; Computational biology; Disease; Gene regulatory network; Genomics; Systems biology; Genetic association; Genome; Genetics; Gene; Medicine; Single-nucleotide polymorphism; Gene expression","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002007839,0.0002489081,0.0001534531,0.00004204079,0.0003512999,0.00006314682,0.0005535074,0.0004604444,0.00001340145],"category_scores_gemma":[0.0001920586,0.0002644876,0.0001994799,0.00002369847,0.0003375299,0.00001199822,0.000407865,0.0002633834,0.000007074933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003238756,"about_ca_system_score_gemma":0.0004676152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.083674e-7,"about_ca_topic_score_gemma":0.00001735988,"domain_scores_codex":[0.9985428,0.00004131126,0.0003161868,0.0004524699,0.0003248782,0.0003223204],"domain_scores_gemma":[0.9977448,0.000007042663,0.0003525065,0.001332538,0.0003154641,0.0002476304],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003043335,0.0001543411,0.4931541,0.000271302,0.0005086503,0.00008636389,0.00009827656,0.4252361,0.0439504,0.001429781,0.03170134,0.0003660188],"study_design_scores_gemma":[0.0006762128,0.0000376917,0.9641001,0.00003168253,0.000127812,0.000002598452,0.00001394064,0.01901481,0.0105995,0.003037789,0.002034774,0.0003230573],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942499,0.002254664,0.001484939,0.00004653258,0.0007906081,0.0003101718,0.0001979782,0.00001933006,0.0006458299],"genre_scores_gemma":[0.9962726,0.0002563594,0.0008955681,0.0001718523,0.001099291,0.00002918781,0.0001602113,0.00005151992,0.001063406],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.470946,"threshold_uncertainty_score":0.9999807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005918687323338161,"score_gpt":0.2263174284773962,"score_spread":0.220398741154058,"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."}}