{"id":"W4213165518","doi":"10.1093/jcag/gwab049.096","title":"A97 DEVELOPMENT OF PREDICTION MODELS FOR THE TRIAGING OF REFERRALS OF INDIVIDUALS WITH SUSPECTED INFLAMMATORY BOWEL DISEASE TO IMPROVE PROMPT ACCESS TO CARE","year":2022,"lang":"en","type":"article","venue":"Journal of the Canadian Association of Gastroenterology","topic":"Inflammatory Bowel Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Referral; Inflammatory bowel disease; Logistic regression; Triage; Ulcerative colitis; Disease; Crohn's disease; Internal medicine; Retrospective cohort study; Abdominal pain; Cohort; Univariate analysis; Family history; Colonoscopy; Multivariate analysis; Emergency medicine; Family medicine; Colorectal cancer; Cancer","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.007475435,0.00164488,0.001058344,0.004139356,0.0007037055,0.002146642,0.001511667,0.001159551,0.00359433],"category_scores_gemma":[0.0212581,0.0006052237,0.001937088,0.001655001,0.0003608788,0.0008961816,0.001180524,0.001953965,0.0009741232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001239458,"about_ca_system_score_gemma":0.00246017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02152847,"about_ca_topic_score_gemma":0.01436162,"domain_scores_codex":[0.9980095,0.0009989444,0.0001672464,0.0004035028,0.0002130669,0.0002077354],"domain_scores_gemma":[0.9828073,0.0128621,0.00147235,0.0004303244,0.001869347,0.0005585332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009040304,0.001216942,0.6602398,0.0002196117,0.0009973292,0.000501229,0.0003113037,0.2469276,0.0005673841,0.001897518,0.01066708,0.07555024],"study_design_scores_gemma":[0.00004986376,0.0001578832,0.02237723,0.00006298784,0.0001888527,0.000101687,0.0001319766,0.9745141,0.0001798072,0.001512942,0.000700907,0.00002165924],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7559566,0.001550826,0.2200243,0.004744784,0.000605849,0.0009094255,0.009042271,0.002535299,0.004630579],"genre_scores_gemma":[0.9480006,0.0003209134,0.04503193,0.0002146997,0.0001500337,0.0004445603,0.004621917,0.00005361727,0.001161593],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02152847,"threshold_uncertainty_score":0.04280633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0097527739921024,"score_gpt":0.2333863481243665,"score_spread":0.2236335741322641,"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."}}