{"id":"W2566998619","doi":"10.2215/cjn.12151116","title":"Screening Women with CKD for the Emperor of All Maladies","year":2016,"lang":"en","type":"letter","venue":"Clinical Journal of the American Society of Nephrology","topic":"Dialysis and Renal Disease Management","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; National Institutes of Health","keywords":"Medicine; Internal medicine; Nephrology; Kidney disease; Population; Guideline; Comorbidity; Cancer; Dialysis; Life expectancy; Disease; Cancer screening; Intensive care medicine; Pathology; Environmental health","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004072773,0.0001423808,0.0002644322,0.0004428705,0.000900771,0.0005071844,0.0003054639,0.0004865076,0.003935876],"category_scores_gemma":[0.002759336,0.0001093821,0.0003095185,0.0005459902,0.0002256867,0.0004065266,0.0004612652,0.0007268068,0.0004634088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001072556,"about_ca_system_score_gemma":0.001493096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09676446,"about_ca_topic_score_gemma":0.2178053,"domain_scores_codex":[0.999679,0.00004667009,0.00001959243,0.0000390994,0.0001480634,0.0000677799],"domain_scores_gemma":[0.9992226,0.0001730067,0.0002695031,0.00004519217,0.0001719431,0.00011772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001347219,0.00008633352,0.8314651,0.0001896547,0.00005571729,0.0003057623,0.000447095,0.00003828013,0.00050833,0.0003122828,0.06386583,0.1025909],"study_design_scores_gemma":[0.00004769782,0.0001427921,0.9514775,0.0003964396,0.0001532925,0.001504559,0.0007052293,0.0002489973,0.000199354,0.0003502224,0.04475219,0.00002170566],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"editorial","genre_scores_codex":[0.7173581,0.04578427,0.002540119,0.1069521,0.004908645,0.0008104367,0.02287436,0.0003210113,0.098451],"genre_scores_gemma":[0.9631789,0.01200471,0.001951668,0.01327397,0.001972455,0.0001065903,0.002048173,0.00001728674,0.005446285],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.09676446,"threshold_uncertainty_score":0.1924024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05159824574362929,"score_gpt":0.3496769635439287,"score_spread":0.2980787178002994,"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."}}