{"id":"W2168965054","doi":"10.1161/strokeaha.114.006609","title":"Polygenic Overlap Between Kidney Function and Large Artery Atherosclerotic Stroke","year":2014,"lang":"en","type":"article","venue":"Stroke","topic":"Chronic Kidney Disease and Diabetes","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Human Genome Research Institute; National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; Canadian Institutes of Health Research; National Institutes of Health; Wellcome Trust","keywords":"Medicine; Renal function; Cystatin C; Creatinine; Internal medicine; Kidney disease; Cardiology; Stroke (engine); Coronary artery disease; Etiology; Genome-wide association study; Heritability; Epidemiology; Urinary system; Single-nucleotide polymorphism; Genotype; Genetics; Gene; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.002812907,0.0004392951,0.0007138552,0.001312696,0.0004543047,0.0009024153,0.0004979949,0.0005715787,0.001823205],"category_scores_gemma":[0.004693043,0.0003862361,0.001732432,0.001893002,0.000715166,0.0003834729,0.001036616,0.0004982461,0.0001027949],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003302289,"about_ca_system_score_gemma":0.0004777766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00737283,"about_ca_topic_score_gemma":0.00882648,"domain_scores_codex":[0.9976135,0.001210907,0.000170881,0.0005577495,0.0002090927,0.0002378384],"domain_scores_gemma":[0.9941996,0.002463393,0.00171426,0.0009961836,0.0002744327,0.0003520504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002831173,0.00002637013,0.9886466,0.00006300204,0.003582068,0.0002241146,0.00007979623,0.001184295,0.001211414,0.0003762783,0.0001190324,0.004203869],"study_design_scores_gemma":[0.000008127422,0.0000395053,0.9966227,0.0000134116,0.0008412066,0.0002103736,0.00002741049,0.001350637,0.00007290924,0.0007186629,0.00008856134,0.000006433834],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.992912,0.002582237,0.002907812,0.0002893682,0.00001546384,0.00001329123,0.0003829285,0.00003587292,0.0008610375],"genre_scores_gemma":[0.9993193,0.0002295438,0.0002092052,0.0000259096,0.00001132316,0.000003761825,0.0001451788,0.00000271965,0.00005304141],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00737283,"threshold_uncertainty_score":0.01487625,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009929190987101877,"score_gpt":0.2339857600313626,"score_spread":0.2240565690442608,"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."}}