{"id":"W4403299607","doi":"10.1097/ccm.0000000000006432","title":"Adjudication of Codes for Identifying Sepsis in Hospital Administrative Data by Expert Consensus*","year":2024,"lang":"en","type":"article","venue":"Critical Care Medicine","topic":"Sepsis Diagnosis and Treatment","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; University of British Columbia; St. Paul's Hospital; McMaster University; University of Ottawa; Canadian Institute for Health Information; Université de Montréal; University of Alberta; University of Calgary; Veterans Affairs Canada; University of Manitoba","funders":"Agency for Healthcare Research and Quality; National Institutes of Health; University of Manitoba; Centers for Disease Control and Prevention; Canadian Institutes of Health Research; U.S. Department of Veterans Affairs","keywords":"Medicine; Diagnosis code; Sepsis; Incidence (geometry); Population; Organ dysfunction; Cohort; Emergency medicine; Intensive care medicine; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.1368758,0.0007918865,0.001431313,0.0114747,0.002466579,0.002523547,0.003171957,0.001474393,0.001629002],"category_scores_gemma":[0.2582521,0.0006819924,0.001276659,0.006326727,0.001478007,0.001313237,0.004860064,0.001324053,0.0005965679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009318518,"about_ca_system_score_gemma":0.03595619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06460189,"about_ca_topic_score_gemma":0.1009739,"domain_scores_codex":[0.8125343,0.09796762,0.03240341,0.009884642,0.042948,0.004262117],"domain_scores_gemma":[0.5877185,0.1327297,0.08318385,0.02587439,0.1653364,0.005157041],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002231383,0.0005433813,0.6937362,0.004899152,0.0009065804,0.0002306782,0.003899818,0.003803313,0.002996986,0.003877119,0.06104182,0.2218336],"study_design_scores_gemma":[0.003394016,0.001145636,0.8546385,0.005919212,0.001033876,0.0006565297,0.003811221,0.04293352,0.007677443,0.005722589,0.07257432,0.0004930648],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6708258,0.006079989,0.1732981,0.01055904,0.001423848,0.06452214,0.03166621,0.001189739,0.04043512],"genre_scores_gemma":[0.7306191,0.001192123,0.218419,0.004337498,0.0005739692,0.01899687,0.02350278,0.0001848724,0.002173804],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1368758,"threshold_uncertainty_score":0.723877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2338087401489657,"score_gpt":0.4955404644088049,"score_spread":0.2617317242598391,"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."}}