{"id":"W4410382811","doi":"10.1136/bmjhci-2024-101381","title":"Assessing the validity of ICD-10 administrative data in coding comorbidities","year":2025,"lang":"en","type":"article","venue":"BMJ Health & Care Informatics","topic":"Medical Coding and Health Information","field":"Health Professions","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health Services; University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Comorbidity; Medicine; Coding (social sciences); ICD-10; Chart; Diabetes mellitus; Data quality; Diagnosis code; Psychiatry; Environmental health; Statistics; Operations management; Population","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00720772,0.0001725981,0.0005357459,0.0002308634,0.001205029,0.00004053017,0.0006635432,0.0002203916,0.000165727],"category_scores_gemma":[0.003009711,0.0001259222,0.00003869744,0.000522488,0.0001479459,0.0008537425,0.0004042144,0.001165969,0.00006355353],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005331502,"about_ca_system_score_gemma":0.007162371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005188968,"about_ca_topic_score_gemma":0.0007718239,"domain_scores_codex":[0.9947509,0.0008372271,0.003096091,0.0001180605,0.0005654217,0.0006323257],"domain_scores_gemma":[0.9939569,0.003045393,0.001488113,0.0009523617,0.0003986488,0.0001585616],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001276852,0.00009477156,0.06986273,0.06146377,0.00004866557,0.000002896666,0.3048097,0.00008980057,8.547033e-7,0.03427732,0.4737745,0.05544728],"study_design_scores_gemma":[0.001818162,0.0002276272,0.06348143,0.008392527,0.0000309123,0.000003266783,0.6309065,0.02580469,0.0000161757,0.0004730524,0.2685612,0.0002843996],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2944966,0.001610517,0.05704563,0.07341387,0.008619677,0.015699,0.001642624,0.0005386616,0.5469335],"genre_scores_gemma":[0.9786822,0.0002296797,0.003911796,0.01564794,0.0001909135,0.0001590745,0.0007115731,0.00001113307,0.0004557122],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6841856,"threshold_uncertainty_score":0.9984661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.579570672031253,"score_gpt":0.6146886480568645,"score_spread":0.03511797602561151,"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."}}