{"id":"W4318765551","doi":"10.1371/journal.pgph.0001467","title":"National health policies and strategies for addressing chronic kidney disease: Data from the International Society of Nephrology Global Kidney Health Atlas","year":2023,"lang":"en","type":"article","venue":"PLOS Global Public Health","topic":"Chronic Kidney Disease and Diabetes","field":"Medicine","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of British Columbia; St. Michael's Hospital; University of Calgary; University of Alberta","funders":"Medical Research Council; Relypsa; Astellas Pharma; International Society of Nephrology; Gilead Sciences; Novo Nordisk; Sanofi; Servier; Amgen; Pfizer; National Health and Medical Research Council; Fresenius Medical Care North America; AstraZeneca; Eli Lilly and Company","keywords":"Kidney disease; Medicine; Government (linguistics); Nephrology; Global health; Health care; Public health; Population; Health policy; Environmental health; Economic growth; Internal medicine; Pathology; Economics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.005743789,0.0006336319,0.0005622417,0.007162402,0.0004475242,0.001547584,0.000807039,0.0004807947,0.003866231],"category_scores_gemma":[0.01773603,0.0003204122,0.0007454921,0.01711005,0.0003959655,0.002105869,0.00208242,0.0009660513,0.0009428558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002158981,"about_ca_system_score_gemma":0.006636418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03544786,"about_ca_topic_score_gemma":0.02710306,"domain_scores_codex":[0.9959564,0.0008851027,0.001032644,0.0002523154,0.001447011,0.0004264456],"domain_scores_gemma":[0.9821787,0.004876002,0.00582629,0.0006352547,0.005299977,0.001183823],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001532538,0.0001130416,0.5800679,0.007012445,0.0004249057,0.0001427118,0.003101237,0.001997024,0.0002597686,0.005857665,0.2953916,0.1054783],"study_design_scores_gemma":[0.00003883221,0.00005485199,0.7686733,0.002268375,0.0001713243,0.000176036,0.003266453,0.0006050582,0.0002612284,0.000897242,0.2235352,0.00005212941],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.1866695,0.01607346,0.002543493,0.01114174,0.0005482877,0.0006957928,0.7248337,0.0003754108,0.05711856],"genre_scores_gemma":[0.4486043,0.02760086,0.01233615,0.00465484,0.0003290483,0.002241367,0.5005723,0.0001508137,0.00351027],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03544786,"threshold_uncertainty_score":0.07048309,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1405724359749543,"score_gpt":0.3989922578794218,"score_spread":0.2584198219044676,"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."}}