{"id":"W2607372085","doi":"10.23889/ijpds.v1i1.71","title":"Developing and Validating Electronic Medical Record Based Case Definitions for Liver Diseases and Comorbidities","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Medicine; Comorbidity; Electronic medical record; Cirrhosis; Diabetes mellitus; Gold standard (test); Medical record; Liver disease; Internal medicine; Electronic health record; Kappa; Hepatitis C; Disease; Emergency medicine; Health care","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":[0.1041425,0.0008005716,0.0008480662,0.01087808,0.001115892,0.003337835,0.002742478,0.001153806,0.002409821],"category_scores_gemma":[0.2340725,0.0006967577,0.001479715,0.005311896,0.00116639,0.003317642,0.003799901,0.0009815622,0.0006576486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003126038,"about_ca_system_score_gemma":0.004337453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005224027,"about_ca_topic_score_gemma":0.005336329,"domain_scores_codex":[0.8895748,0.05472854,0.03182251,0.006683509,0.01538313,0.001807636],"domain_scores_gemma":[0.7508523,0.111373,0.0580351,0.02849399,0.04970591,0.00153972],"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":[0.0002112765,0.0002863406,0.945933,0.000508472,0.0001910855,0.000294808,0.001215974,0.001882024,0.000631434,0.002061039,0.004424634,0.04235993],"study_design_scores_gemma":[0.0004240691,0.0005824068,0.8824835,0.002224591,0.0004274875,0.001594586,0.004968563,0.07403259,0.009479925,0.004036283,0.01960206,0.0001439157],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8686529,0.001750049,0.09699023,0.001942781,0.0005837754,0.01038483,0.01069581,0.0004664622,0.008533126],"genre_scores_gemma":[0.806809,0.0006089768,0.1699135,0.0006165702,0.0002141029,0.00692893,0.01418387,0.00005776559,0.0006672224],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.1041425,"threshold_uncertainty_score":0.5507646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2594944024115622,"score_gpt":0.4585644835940625,"score_spread":0.1990700811825003,"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."}}