{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001475666,0.0005205148,0.0005616663,0.0008582486,0.0001853358,0.0005761442,0.0003449742,0.0006088156,0.002270092],"category_scores_gemma":[0.006346423,0.000337861,0.00126095,0.0006491443,0.0003087761,0.0004025397,0.0006494104,0.000910783,0.0002208174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002917492,"about_ca_system_score_gemma":0.00037811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00553385,"about_ca_topic_score_gemma":0.004232851,"domain_scores_codex":[0.998515,0.000741095,0.00007537853,0.0002343706,0.0002324507,0.0002018104],"domain_scores_gemma":[0.9978234,0.0009399789,0.0005751447,0.0002782659,0.0002528949,0.0001304278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003333027,0.00006964418,0.9841554,0.00009016279,0.001580116,0.0002070368,0.00004246967,0.001427751,0.000787756,0.0002610087,0.000419277,0.01062609],"study_design_scores_gemma":[0.00001087166,0.0001408709,0.9967358,0.00001368365,0.0004317788,0.0002610669,0.00003536207,0.001351295,0.0002001933,0.0002698546,0.0005430272,0.000006260215],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9791783,0.007522405,0.004491482,0.0007477794,0.00009882951,0.00006815988,0.002621605,0.0001809301,0.005090307],"genre_scores_gemma":[0.99756,0.0008752458,0.0004409604,0.00006953855,0.00007475811,0.00001778974,0.0006121854,0.000008360571,0.000341094],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00553385,"threshold_uncertainty_score":0.01100326,"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."}}