{"id":"W4298277439","doi":"10.1136/annrheumdis-2022-eular.2967","title":"POS0155 WHAT DRIVES RACIAL DISPARITIES IN GOUT IN THE US? – POPULATION-BASED, SEX-SPECIFIC, CASUAL MEDIATION ANALYSIS","year":2022,"lang":"en","type":"article","venue":"Annals of the Rheumatic Diseases","topic":"Gout, Hyperuricemia, Uric Acid","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Research Canada","funders":"","keywords":"Medicine; Gout; National Health and Nutrition Examination Survey; Population; Body mass index; Hyperuricemia; Demography; Gerontology; Internal medicine; Kidney disease; Cohort; Health equity; Mediation; Public health; Environmental health; Uric acid; Pathology","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":[0.005606577,0.001312671,0.001131585,0.0007411336,0.001434341,0.001974538,0.002250079,0.002885107,0.01774138],"category_scores_gemma":[0.01621205,0.0007965401,0.005535792,0.001124054,0.0009490814,0.001324055,0.002392712,0.003409205,0.001093682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004803412,"about_ca_system_score_gemma":0.002065342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02666106,"about_ca_topic_score_gemma":0.01288829,"domain_scores_codex":[0.9926662,0.004510803,0.0002557897,0.001116976,0.0002944386,0.001155735],"domain_scores_gemma":[0.991979,0.00492575,0.0008585143,0.001277575,0.0003467855,0.0006123013],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01282839,0.001136088,0.9437965,0.0004219918,0.01616616,0.0008163811,0.001444795,0.001283716,0.0009443207,0.004479009,0.004960518,0.0117222],"study_design_scores_gemma":[0.003798021,0.005426856,0.8748109,0.0007328208,0.0475156,0.001594717,0.008381272,0.02194664,0.001516051,0.02173866,0.01234295,0.000195536],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9795176,0.003531176,0.003329038,0.004352153,0.0007188401,0.0001431406,0.003487904,0.00009225315,0.004827942],"genre_scores_gemma":[0.9959742,0.0002907696,0.00054683,0.0004711484,0.0001552649,0.0001073224,0.0004876909,0.00002014708,0.001946545],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02666106,"threshold_uncertainty_score":0.05935085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02691311675244206,"score_gpt":0.2993930760496548,"score_spread":0.2724799592972127,"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."}}