{"id":"W4323528522","doi":"10.2139/ssrn.4376992","title":"Identifying Long Covid Using Electronic Health Records: A National Observational Cohort Study in Scotland","year":2023,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Long-Term Effects of COVID-19","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute of Population and Public Health","funders":"","keywords":"Medicine; Poisson regression; Cohort; Population; Demography; Coronavirus disease 2019 (COVID-19); Cohort study; Observational study; Family medicine; Pediatrics; Internal medicine; Environmental health","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":[0.003855105,0.0005995148,0.0008941909,0.001577968,0.001736736,0.003166974,0.001479164,0.001518023,0.002824102],"category_scores_gemma":[0.01221563,0.001146042,0.001523755,0.004665357,0.0008624225,0.002528346,0.002986185,0.002593346,0.0006595367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002571866,"about_ca_system_score_gemma":0.003759914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2183933,"about_ca_topic_score_gemma":0.2306684,"domain_scores_codex":[0.995282,0.001144578,0.0005832798,0.0008062025,0.0008801909,0.001303681],"domain_scores_gemma":[0.9889793,0.001255244,0.00481404,0.001425224,0.001740075,0.001786091],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001532099,0.00007974513,0.9975722,0.000019654,0.0001597938,0.00009936051,0.000371629,0.00001645348,0.0000784478,0.00007606068,0.0005765784,0.0007967979],"study_design_scores_gemma":[0.00002091053,0.0000749809,0.9984484,0.00002571753,0.00005257053,0.00007347513,0.0007422448,0.00007952037,0.00001282976,0.00003745659,0.0004198576,0.00001210398],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946511,0.0007957708,0.000163865,0.0004873353,0.00005406792,0.0000264988,0.003275753,0.000008602532,0.0005370447],"genre_scores_gemma":[0.9959515,0.0004271452,0.0002109254,0.0003004869,0.00005072211,0.00004268364,0.002350694,0.00001076845,0.0006549929],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2183933,"threshold_uncertainty_score":0.4342442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08178789640969651,"score_gpt":0.4044443014292214,"score_spread":0.3226564050195249,"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."}}