{"id":"W4387495437","doi":"10.1287/opre.2020.0685","title":"Distributionally Robust Optimization Under Distorted Expectations","year":2023,"lang":"en","type":"article","venue":"Operations Research","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; University of Waterloo","funders":"","keywords":"Ambiguity; Cumulative prospect theory; Robust optimization; Distortion (music); Expected utility hypothesis; Computer science; Mathematical optimization; Risk aversion (psychology); Prospect theory; Class (philosophy); Optimal decision; Convex optimization; Subjective expected utility; Economics; Econometrics; Regular polygon; Mathematical economics; Microeconomics; Mathematics; Artificial intelligence","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":[0.004422132,0.00118874,0.001611027,0.0005233183,0.0003565713,0.002630794,0.001098662,0.001535214,0.00175656],"category_scores_gemma":[0.01993568,0.0007621719,0.001082074,0.0006957319,0.001970745,0.003258081,0.001923201,0.002069249,0.0003080152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002212191,"about_ca_system_score_gemma":0.001483448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002758026,"about_ca_topic_score_gemma":0.0009528093,"domain_scores_codex":[0.9968574,0.001511237,0.000166174,0.0005070635,0.0006049679,0.0003531073],"domain_scores_gemma":[0.9925317,0.004880927,0.001008254,0.0006516817,0.0006609334,0.0002665689],"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":[0.0001080699,0.00003031091,0.0003854258,0.00005917677,0.00007618868,0.0001124703,0.00007449072,0.8940569,0.0009400561,0.09613176,0.0006339881,0.007391217],"study_design_scores_gemma":[0.00001404878,0.00003244484,0.0001581351,0.00000884057,0.000007990797,0.00001624587,0.00001785628,0.9122947,0.0003718069,0.08685204,0.0002135553,0.00001241611],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0800954,0.0005368381,0.9090735,0.001584788,0.00006188472,0.00005017201,0.0001425377,0.0001398187,0.008315072],"genre_scores_gemma":[0.9387199,0.0005244698,0.05717617,0.0002166616,0.00005764985,0.00008862989,0.0001584451,0.00006960348,0.002988547],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004422132,"threshold_uncertainty_score":0.02338672,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4007544570497615,"score_gpt":0.5133885084234063,"score_spread":0.1126340513736449,"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."}}