{"id":"W4388837354","doi":"10.1093/aje/kwad232","title":"Inconsistency in UK Biobank Event Definitions From Different Data Sources and Its Impact on Bias and Generalizability: A Case Study of Venous Thromboembolism","year":2023,"lang":"en","type":"article","venue":"American Journal of Epidemiology","topic":"Venous Thromboembolism Diagnosis and Management","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Medical Research Council; Chief Scientist Office, Scottish Government Health and Social Care Directorate; NIHR Cambridge Biomedical Research Centre; Economic and Social Research Council; European Commission; Department of Health and Social Care; Health and Social Care Research and Development Division; Novo Nordisk; National Institute for Health and Care Research; Engineering and Physical Sciences Research Council; UK Research and Innovation; School of Public Health, Imperial College London; Public Health Agency; British Heart Foundation; Scottish Government; European Federation of Pharmaceutical Industries and Associations; Imperial College London; Wellcome Trust","keywords":"Medicine; Generalizability theory; Biobank; Pulmonary embolism; Deep vein; Concordance; Representativeness heuristic; Emergency medicine; Disease; Data source; Intensive care medicine; Thrombosis; Internal medicine; Data mining","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2819472,0.0008141292,0.002182583,0.004132445,0.003738197,0.004771088,0.003522078,0.004433944,0.00162302],"category_scores_gemma":[0.5670763,0.001624272,0.002632928,0.00890498,0.005847102,0.004635748,0.006390171,0.002983634,0.0002128906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006102844,"about_ca_system_score_gemma":0.003539931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04004979,"about_ca_topic_score_gemma":0.02882024,"domain_scores_codex":[0.4530915,0.4762965,0.03283451,0.01174078,0.02180771,0.004229087],"domain_scores_gemma":[0.2420485,0.6314691,0.05891563,0.04756838,0.01883652,0.001161919],"domain_codex":"methods","domain_gemma":"methods","domain_candidate":"methods","domain_consensus":"methods","study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002272715,0.0004845158,0.9156235,0.0009485291,0.002232672,0.004334943,0.03271257,0.001175678,0.000289603,0.005468469,0.00218868,0.03226809],"study_design_scores_gemma":[0.001445445,0.002593296,0.877444,0.005011661,0.005917645,0.02551293,0.03303596,0.01915952,0.002376767,0.01352867,0.01336901,0.0006051493],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9726641,0.005219885,0.01420707,0.003280861,0.00008951623,0.001040228,0.0005828257,0.00002288294,0.002892744],"genre_scores_gemma":[0.98691,0.0006705034,0.01062713,0.0007397385,0.00006227699,0.0005500327,0.0002713923,0.00002503489,0.000143838],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7180528,"threshold_uncertainty_score":0.885487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1878479291167263,"score_gpt":0.4088795995582014,"score_spread":0.2210316704414751,"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."}}