{"id":"W2792996849","doi":"10.5539/gjhs.v10n4p85","title":"Biochemical Markers Present in a Population Susceptible to Suffering From Metabolic Syndrome","year":2018,"lang":"en","type":"article","venue":"Global Journal of Health Science","topic":"Gout, Hyperuricemia, Uric Acid","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metabolic syndrome; Abdominal obesity; Uric acid; Waist; Medicine; Context (archaeology); Obesity; Population; Internal medicine; Lipid profile; Confidence interval; Cross-sectional study; National Cholesterol Education Program; Demography; Endocrinology; Cholesterol; Environmental health; Biology; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001505813,0.0002690186,0.0003626117,0.0008258365,0.0005140878,0.0005956326,0.0001686774,0.0003326604,0.001798823],"category_scores_gemma":[0.0009009066,0.0001946629,0.0001561035,0.0007018045,0.0002241621,0.0001821296,0.0002580081,0.0002808604,0.0001697006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001782713,"about_ca_system_score_gemma":0.0002202894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007879003,"about_ca_topic_score_gemma":0.008087814,"domain_scores_codex":[0.9998228,0.00003348916,0.00001579572,0.0000486785,0.00004151711,0.00003770944],"domain_scores_gemma":[0.9996873,0.00004595419,0.0001412527,0.00001907354,0.00003909686,0.0000674253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005995687,0.00004539012,0.9983302,0.00001050833,0.00001974949,0.0001970407,0.0001361782,0.00001172165,0.0003829807,0.00001186161,0.00004619594,0.0007483049],"study_design_scores_gemma":[0.000002881284,0.00005904076,0.9990795,0.000003916944,0.0000132252,0.0003949016,0.0002930887,0.00003326032,0.00002197647,0.00001317999,0.00008341046,0.000001602985],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992384,0.0001901783,0.00003935336,0.00002146777,0.00000360346,0.000007098879,0.000126229,0.000001817544,0.0003718552],"genre_scores_gemma":[0.9995054,0.00009392321,0.0000574416,0.00001470417,0.000008681463,0.000007783407,0.000182934,8.555663e-7,0.0001283079],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007879003,"threshold_uncertainty_score":0.01566625,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02167629859901293,"score_gpt":0.3439541715021169,"score_spread":0.3222778729031039,"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."}}