{"id":"W4388831596","doi":"10.1002/ajim.23550","title":"Using the Functional Comorbidity Index with administrative workers’ compensation data: Utility, validity, and caveats","year":2023,"lang":"en","type":"article","venue":"American Journal of Industrial Medicine","topic":"Frailty in Older Adults","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; Canadian Memorial Chiropractic College; University of Toronto","funders":"National Institute for Occupational Safety and Health; National Institute of Arthritis and Musculoskeletal and Skin Diseases; University of Washington","keywords":"Medicine; Confounding; Comorbidity; Concordance; National Comorbidity Survey; Workers' compensation; External validity; Predictive validity; Gerontology; Statistics; Compensation (psychology); Clinical psychology; Psychiatry; Internal medicine; Psychology","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":[0.1669023,0.001839051,0.001794537,0.004721245,0.001764811,0.005755208,0.0056993,0.002993628,0.001079034],"category_scores_gemma":[0.3497636,0.001122563,0.003342397,0.009917067,0.00467638,0.003945236,0.003345718,0.004640313,0.0004438596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002596735,"about_ca_system_score_gemma":0.00448581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0319033,"about_ca_topic_score_gemma":0.03831876,"domain_scores_codex":[0.848955,0.1076803,0.01032814,0.006603951,0.02535613,0.001076651],"domain_scores_gemma":[0.6311402,0.2960935,0.02628135,0.02345131,0.02179291,0.001240748],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002858764,0.00007604907,0.9384292,0.0005525377,0.001919273,0.0002071864,0.0009242369,0.002323982,0.00017838,0.002808043,0.004545762,0.04774945],"study_design_scores_gemma":[0.000279238,0.001211474,0.8348883,0.005283033,0.00232924,0.003258627,0.002820405,0.08954971,0.002616843,0.03723913,0.0200018,0.0005221324],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6345611,0.03254368,0.2253417,0.07063943,0.004681673,0.002252838,0.006962994,0.0007640959,0.02225249],"genre_scores_gemma":[0.9104078,0.002368905,0.07804353,0.004577652,0.001319644,0.0009387734,0.00135383,0.0001420592,0.0008477751],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1669023,"threshold_uncertainty_score":0.8826742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.455872098461047,"score_gpt":0.4121045607452876,"score_spread":0.04376753771575947,"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."}}