{"id":"W3028631995","doi":"10.1093/ecco-jcc/jjaa103","title":"Appraisal of the PIBD-classes Criteria: A Multicentre Validation","year":2020,"lang":"en","type":"article","venue":"Journal of Crohn s and Colitis","topic":"Inflammatory Bowel Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children","funders":"","keywords":"Ulcerative colitis; Inflammatory bowel disease; Cohort; Medicine; Algorithm; Disease; Artificial intelligence; Crohn's disease; Gastroenterology; Internal medicine; Mathematics; Computer science","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":[0.04933748,0.001146477,0.00130192,0.00206992,0.0007118854,0.001501469,0.002531932,0.001022902,0.001291019],"category_scores_gemma":[0.09085582,0.0005798145,0.001858107,0.002118069,0.001034839,0.001134278,0.002529911,0.0007284897,0.000639041],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001789531,"about_ca_system_score_gemma":0.00330845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004319021,"about_ca_topic_score_gemma":0.003445411,"domain_scores_codex":[0.9736794,0.01553812,0.002843446,0.002208957,0.005162165,0.0005680086],"domain_scores_gemma":[0.9473883,0.01952339,0.007932572,0.007247865,0.01665353,0.001254288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.009964341,0.0009744096,0.8670523,0.00195222,0.001202519,0.0005183193,0.002464887,0.00432992,0.002320338,0.0007299783,0.004225519,0.1042653],"study_design_scores_gemma":[0.004398549,0.007309548,0.9588485,0.001058016,0.001008297,0.001423965,0.0008175647,0.01306806,0.001985396,0.0005244351,0.009453251,0.0001043098],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9686787,0.002041082,0.01508468,0.0002256889,0.0001610451,0.009410474,0.001964197,0.00007430502,0.002359719],"genre_scores_gemma":[0.9558257,0.0006141305,0.03129487,0.0001546135,0.00008631789,0.006301699,0.005242274,0.0000656526,0.0004146654],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04933748,"threshold_uncertainty_score":0.2609246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01033200253855636,"score_gpt":0.265249593785026,"score_spread":0.2549175912464696,"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."}}