{"id":"W2804163236","doi":"10.3390/pr6050060","title":"EPO Dosage Optimization for Anemia Management: Stochastic Control under Uncertainty Using Conditional Value at Risk","year":2018,"lang":"en","type":"article","venue":"Processes","topic":"Erythropoietin and Anemia Treatment","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"CVAR; Erythropoietin; Dosing; Medicine; Model predictive control; Anemia; Mathematical optimization; Expected shortfall; Controller (irrigation); Computer science; Control theory (sociology); Control (management); Mathematics; Risk management; Internal medicine; Artificial intelligence; Economics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009451052,0.0001542338,0.0001900348,0.00006282716,0.0003169944,0.00002238326,0.00004827031,0.00006321336,0.000400508],"category_scores_gemma":[0.00009540006,0.0001261075,0.00004933881,0.0001466386,0.000157119,0.00006746892,0.00002209494,0.000050461,0.00002402886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001963547,"about_ca_system_score_gemma":0.0001037868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002109583,"about_ca_topic_score_gemma":0.00001112275,"domain_scores_codex":[0.9991006,0.00001696736,0.0001838941,0.0002778088,0.0001949994,0.0002257877],"domain_scores_gemma":[0.9992483,0.0001382671,0.0001244912,0.0001281149,0.0002764255,0.00008435376],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001955708,0.000760433,0.004587921,0.005604637,0.0007324545,0.00003554084,0.0005163528,0.9796727,0.000432351,0.002086358,0.002376191,0.001239365],"study_design_scores_gemma":[0.03610133,0.002276807,0.001911137,0.00161764,0.00502759,0.0003409385,0.001460865,0.9290348,0.004407873,0.01274442,0.004038034,0.001038601],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08196001,0.0009216678,0.9131251,0.0007867934,0.0001636487,0.001384191,0.0002051416,0.0001315128,0.001321955],"genre_scores_gemma":[0.9778632,0.0001057754,0.02005028,0.0005518267,0.0003211192,0.00009814117,0.0003632515,0.00002709776,0.0006193193],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8959032,"threshold_uncertainty_score":0.5142514,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01831890127545708,"score_gpt":0.2948243252624909,"score_spread":0.2765054239870338,"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."}}