{"id":"W4234410517","doi":"10.1093/ibd/izy037.037","title":"P164 USING EXOME SEQUENCING TO EXPAND THE GENETIC ARCHITECTURE OF INFLAMMATORY BOWEL DISEASE","year":2018,"lang":"en","type":"article","venue":"Inflammatory Bowel Diseases","topic":"Inflammatory Bowel Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Exome sequencing; Genome-wide association study; Exome; Genetic architecture; Genetics; Biology; NOD2; Genetic association; Population; Allele; Inflammatory bowel disease; Computational biology; Gene; Disease; Medicine; Single-nucleotide polymorphism; Phenotype; Genotype","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001530997,0.0005716853,0.0006257425,0.00245389,0.0004347834,0.001335933,0.0004704348,0.001152959,0.004720204],"category_scores_gemma":[0.004307594,0.0003468617,0.0007711757,0.002258382,0.0003761399,0.001027568,0.00179342,0.001923083,0.001124517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002895868,"about_ca_system_score_gemma":0.0004354564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001247605,"about_ca_topic_score_gemma":0.001756767,"domain_scores_codex":[0.9993789,0.000177141,0.00005555848,0.0002001984,0.0001297021,0.00005840866],"domain_scores_gemma":[0.9981104,0.0009966749,0.0002154882,0.0002951437,0.0002235018,0.0001587908],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001951438,0.0002926374,0.2754362,0.002732955,0.002804318,0.01491616,0.001959647,0.008911896,0.1903628,0.01694345,0.04182079,0.4418677],"study_design_scores_gemma":[0.0005483006,0.0008068563,0.5574774,0.00165384,0.001455367,0.02535659,0.001008487,0.01800085,0.01647967,0.096205,0.2807709,0.0002366692],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7478436,0.03918909,0.1288617,0.01643245,0.001725137,0.0005108473,0.04191213,0.0009405314,0.02258456],"genre_scores_gemma":[0.8646955,0.02140892,0.07074722,0.009184607,0.002021298,0.0005223103,0.02527119,0.0004878933,0.005661068],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004720204,"threshold_uncertainty_score":0.0157907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01114399235397533,"score_gpt":0.2446188843467206,"score_spread":0.2334748919927453,"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."}}