{"id":"W2971414197","doi":"10.1002/art.41067","title":"Population Impact Attributable to Modifiable Risk Factors for Hyperuricemia","year":2019,"lang":"en","type":"article","venue":"Arthritis & Rheumatology","topic":"Gout, Hyperuricemia, Uric Acid","field":"Medicine","cited_by":138,"is_retracted":false,"has_abstract":true,"ca_institutions":"Research Canada","funders":"National Institute of Arthritis and Musculoskeletal and Skin Diseases; Canadian Institutes of Health Research; National Institutes of Health","keywords":"Hyperuricemia; Medicine; DASH diet; Overweight; Body mass index; Population; Obesity; Diuretic; Dash; Internal medicine; Confidence interval; Risk factor; Gout; Demography; Endocrinology; Uric acid; Environmental health; Blood pressure","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003157708,0.0003599316,0.001132164,0.0002833396,0.0001850618,0.00003561237,0.0001788753,0.0003481485,0.0007820379],"category_scores_gemma":[0.0007640167,0.0003250868,0.0002795676,0.0004235617,0.00004197746,0.0002490877,0.00008857447,0.0003094288,0.001028834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002533367,"about_ca_system_score_gemma":0.0001440022,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007805422,"about_ca_topic_score_gemma":0.00005793779,"domain_scores_codex":[0.9974127,0.00008102856,0.0006136841,0.0006714953,0.0002934322,0.0009276293],"domain_scores_gemma":[0.9980171,0.0004578572,0.0002249927,0.0007286079,0.0001754352,0.0003959775],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002671536,0.0001279888,0.9866282,0.00008242809,0.0001878131,0.000009605143,0.0003652317,0.001526369,0.001696704,0.0005255999,0.005501988,0.003080919],"study_design_scores_gemma":[0.02088401,0.005834043,0.8968005,0.0009101772,0.0005559236,0.003180888,0.001221484,0.01529123,0.006369724,0.003310183,0.0435628,0.002078986],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939225,0.0008907897,0.001273102,0.0003403964,0.000706632,0.001767909,0.0001925819,0.0002212582,0.0006847947],"genre_scores_gemma":[0.9954595,0.0003209709,0.002656047,0.0001708409,0.0000441802,0.0001209253,0.0004565597,0.0000826725,0.0006882814],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08982766,"threshold_uncertainty_score":0.9999201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01129088763967348,"score_gpt":0.2738424887384392,"score_spread":0.2625516010987658,"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."}}