{"id":"W4387965419","doi":"10.1007/s44197-023-00161-w","title":"A Population-Based Outcome-Wide Association Study of the Comorbidities and Sequelae Following COVID-19 Infection","year":2023,"lang":"en","type":"article","venue":"Journal of Epidemiology and Global Health","topic":"Long-Term Effects of COVID-19","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network; Princess Margaret Cancer Centre; University of Toronto","funders":"West China Hospital, Sichuan University","keywords":"Medicine; Coronavirus disease 2019 (COVID-19); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Outcome (game theory); Comorbidity; Betacoronavirus; Population; Coronavirus Infections; Association (psychology); MEDLINE; Intensive care medicine; Virology; Internal medicine; Environmental health; Disease; Outbreak; Infectious disease (medical specialty)","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":[0.001293914,0.0003241174,0.0004639103,0.0009045407,0.0006838614,0.0007728213,0.0004386193,0.0006269394,0.001588129],"category_scores_gemma":[0.002852236,0.0003538676,0.0008759646,0.001652453,0.0002848336,0.0006738748,0.001052054,0.001062067,0.0002460367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002996743,"about_ca_system_score_gemma":0.0005477794,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003911307,"about_ca_topic_score_gemma":0.005109125,"domain_scores_codex":[0.998937,0.0002814916,0.0001331554,0.0003123215,0.0001515698,0.0001845268],"domain_scores_gemma":[0.997833,0.0003141595,0.0009211294,0.0002837223,0.0002541954,0.0003938008],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001148606,0.00002034735,0.9990461,0.00001393684,0.0001197154,0.00004346419,0.00002757516,0.0000136204,0.00007522475,0.00001176618,0.0000784131,0.0004349235],"study_design_scores_gemma":[0.000006107603,0.000093305,0.9993456,0.000008821963,0.00006127506,0.0001581961,0.00009178033,0.00006843398,0.00001374215,0.00001545039,0.0001343935,0.000002910718],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973983,0.0007185267,0.0002083207,0.00006428555,0.00001896515,0.00002018287,0.001147445,0.000004150229,0.0004197889],"genre_scores_gemma":[0.9987682,0.0001995161,0.0001167711,0.00003076227,0.00001788116,0.00002196129,0.0007302336,0.00000239565,0.0001122543],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003911307,"threshold_uncertainty_score":0.007777095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07042200806390023,"score_gpt":0.4506547335586817,"score_spread":0.3802327254947815,"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."}}