{"id":"W2792701741","doi":"10.1097/md.0000000000009960","title":"Chart validation of inpatient International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) administrative diagnosis codes for venous thromboembolism (VTE) among intravenous immune globulin (IGIV) users in the Sentinel Distributed Database","year":2018,"lang":"en","type":"article","venue":"Medicine","topic":"Venous Thromboembolism Diagnosis and Management","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of General Medical Sciences; Hamilton Health Sciences Foundation; Kaiser Permanente; U.S. Department of Health and Human Services","keywords":"Medicine; Medical diagnosis; Pulmonary embolism; Deep vein; Diagnosis code; Medical record; Emergency medicine; Venous thrombosis; Retrospective cohort study; Thrombosis; Pediatrics; Intensive care medicine; Internal medicine; Population; Radiology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001760725,0.000259306,0.001065096,0.0002466002,0.0001076375,0.00001658914,0.0004039699,0.0001240588,0.00011406],"category_scores_gemma":[0.001964703,0.0001868598,0.0001647777,0.000510173,0.0008045727,0.0001649669,0.00008080497,0.0002008134,0.000005366722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001278074,"about_ca_system_score_gemma":0.0001594725,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003356076,"about_ca_topic_score_gemma":0.00004228399,"domain_scores_codex":[0.996483,0.0002707179,0.001706275,0.0005137014,0.0007495924,0.0002766938],"domain_scores_gemma":[0.996618,0.0006039632,0.001068162,0.0007700758,0.0008124094,0.0001274255],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003115995,0.03309605,0.7864114,0.002449577,0.001975039,0.00004808371,0.01775168,0.0001114381,0.009466354,0.01793648,0.08083274,0.04680518],"study_design_scores_gemma":[0.003142166,0.002139438,0.9810981,0.001238536,0.0008145079,0.000004078252,0.002644139,0.00186481,0.003339567,0.0002380431,0.003309118,0.0001675515],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9826218,0.0003871233,0.005255289,0.007857129,0.0005771574,0.002531369,0.000516636,0.00003212584,0.0002213439],"genre_scores_gemma":[0.9912519,0.001527883,0.0003467292,0.0003239625,0.00063403,0.000300511,0.005575089,0.00002645516,0.00001339199],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1946867,"threshold_uncertainty_score":0.7619922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08218458717029786,"score_gpt":0.3866808267103246,"score_spread":0.3044962395400267,"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."}}