{"id":"W4410792350","doi":"10.1093/imamci/dnaf014","title":"Error analysis for approximate CVaR-optimal control with a maximum cost","year":2025,"lang":"en","type":"article","venue":"IMA Journal of Mathematical Control and Information","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Hydro One (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"CVAR; Control (management); Optimal control; Computer science; Mathematical optimization; Mathematics; Expected shortfall; Economics; Risk management; Finance","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008369757,0.00142231,0.00253055,0.0008792627,0.0005255438,0.002395638,0.001664388,0.002401145,0.002360525],"category_scores_gemma":[0.01825921,0.0006728399,0.001014022,0.0007043805,0.002425869,0.001857234,0.00282025,0.002600725,0.0002275381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001915853,"about_ca_system_score_gemma":0.002081325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005743236,"about_ca_topic_score_gemma":0.002083308,"domain_scores_codex":[0.9981496,0.0008598934,0.00009203666,0.0002702562,0.0004751535,0.0001531483],"domain_scores_gemma":[0.9873909,0.009883531,0.0006230092,0.0004440012,0.001413181,0.0002453509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006745139,0.00001734684,0.0001858325,0.00009603055,0.00002615037,0.00002800464,0.0000287404,0.9742895,0.0004525962,0.02027066,0.0002403342,0.004297463],"study_design_scores_gemma":[0.000002307778,0.0000103817,0.00001844992,0.000006879364,0.000002135544,0.000003074914,0.000002371313,0.9976754,0.00009223573,0.002120497,0.00006369502,0.000002525525],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01098015,0.0005477654,0.9858162,0.0003858823,0.00005996099,0.00003250014,0.00003455731,0.00009946173,0.002043446],"genre_scores_gemma":[0.8621108,0.0006168891,0.1321061,0.0002657362,0.0001020802,0.0002682923,0.0001674099,0.0001689689,0.004193656],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008369757,"threshold_uncertainty_score":0.04426402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004608488627225402,"score_gpt":0.2164089809249605,"score_spread":0.2118004922977351,"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."}}