{"id":"W3093129487","doi":"","title":"Identifying Optimal Anemia Management Practices in Hemodialysis","year":2019,"lang":"en","type":"article","venue":"Deep Blue (University of Michigan)","topic":"Erythropoietin and Anemia Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agency for Healthcare Research and Quality; European Renal Association-European Dialysis and Transplant Association; Chulalongkorn University; National Institutes of Health; Kidney Research UK; National Institute for Health and Care Research; Amgen; Cancer Care Ontario; Akebia Therapeutics; National Research Council of Thailand; King Chulalongkorn Memorial Hospital; Kyowa Hakko Kirin; Institut National de la Santé et de la Recherche Médicale; FibroGen; Medical Research Council; Otsuka America; National Health and Medical Research Council; Fresenius Medical Care North America; AstraZeneca","keywords":"Hemodialysis; Anemia; Medicine; Computer science; Intensive care medicine; Internal medicine","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":[0.003073883,0.00009200477,0.0003114467,0.0005103747,0.0003964042,0.0009497043,0.0003453826,0.0004337049,0.0004784736],"category_scores_gemma":[0.01638395,0.000158561,0.0002870393,0.000755591,0.0002275001,0.000701641,0.0005826509,0.0004350301,0.0000650904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009201335,"about_ca_system_score_gemma":0.001872052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00436204,"about_ca_topic_score_gemma":0.005977307,"domain_scores_codex":[0.9978088,0.001208445,0.000273402,0.0003117193,0.0002417924,0.0001559052],"domain_scores_gemma":[0.9954433,0.002105454,0.001623964,0.0002066205,0.0002775167,0.0003430902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004539053,0.0003616318,0.9355708,0.0001685279,0.0001226209,0.00003374816,0.00150777,0.0005344982,0.0003615824,0.0005373626,0.0006974436,0.05965013],"study_design_scores_gemma":[0.00004616858,0.000504491,0.9913293,0.0001655094,0.00008398702,0.0000863807,0.001781887,0.002872054,0.0003928077,0.001413523,0.001307907,0.00001603595],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959527,0.001310318,0.001224691,0.0006508557,0.00001426246,0.00005250003,0.0001833632,0.00001373551,0.0005975487],"genre_scores_gemma":[0.9973894,0.0004759455,0.001822716,0.0001085675,0.00001173527,0.00003314796,0.00009058885,0.000002524568,0.0000653408],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00436204,"threshold_uncertainty_score":0.01625645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01519349096602149,"score_gpt":0.247277804533436,"score_spread":0.2320843135674145,"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."}}