{"id":"W3118343457","doi":"10.1017/s2045796020001080","title":"A Bayesian approach to estimating the population prevalence of mood and anxiety disorders using multiple measures","year":2021,"lang":"en","type":"article","venue":"Epidemiology and Psychiatric Sciences","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Lawson Health Research Institute; Institute for Clinical Evaluative Sciences; Western University","funders":"","keywords":"Anxiety; Concordance; Population; Medical diagnosis; Credible interval; Markov chain Monte Carlo; Medicine; Mental health; Posterior probability; Statistics; Small area estimation; Bayesian probability; Bayes' theorem; Demography; Psychiatry; Mathematics; Environmental health","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.02541443,0.001535369,0.002357362,0.005794401,0.001455355,0.003222296,0.00370476,0.002078019,0.003974313],"category_scores_gemma":[0.0955119,0.00156564,0.003088958,0.00387975,0.002584546,0.003031983,0.00241862,0.003518501,0.0005216313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003282933,"about_ca_system_score_gemma":0.003163706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0317302,"about_ca_topic_score_gemma":0.02749622,"domain_scores_codex":[0.9841457,0.01169318,0.000588993,0.001835519,0.001483104,0.0002534621],"domain_scores_gemma":[0.9479797,0.04564834,0.002417074,0.001635732,0.002028287,0.0002907891],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002669015,0.0002068844,0.03028071,0.0008581132,0.002049197,0.0005687452,0.001826343,0.5404298,0.001217409,0.2341717,0.003874422,0.1842496],"study_design_scores_gemma":[0.00008157782,0.0001078268,0.007239698,0.0003759027,0.0003554628,0.0003488242,0.0002137793,0.7217119,0.0003486233,0.2654725,0.003627909,0.0001159322],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01041383,0.0004675057,0.9871622,0.000354373,0.00002820068,0.0002249355,0.0002715875,0.0001457936,0.000931601],"genre_scores_gemma":[0.245129,0.001274769,0.7482696,0.0003379906,0.0002256057,0.001725701,0.001063188,0.000105352,0.001868805],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0317302,"threshold_uncertainty_score":0.1344059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.083302596653647,"score_gpt":0.3906629189062992,"score_spread":0.3073603222526522,"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."}}