{"id":"W3094948588","doi":"10.1287/moor.2022.1299","title":"Maximum Spectral Measures of Risk with Given Risk Factor Marginal Distributions","year":2022,"lang":"en","type":"article","venue":"Mathematics of Operations Research","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Mathematics; Risk measure; Measure (data warehouse); Upper and lower bounds; Duality (order theory); Mathematical optimization; Applied mathematics; Expected shortfall; Metric (unit); Bellman equation; Function (biology); Wasserstein metric; Constraint (computer-aided design); Combinatorics; Mathematical analysis; Risk management; Computer science; Finance","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.005319627,0.0001114302,0.000308747,0.0006210653,0.001094638,0.0001577967,0.0008105565,0.0000373514,0.002205927],"category_scores_gemma":[0.003941087,0.00007975553,0.00009980876,0.002010639,0.0003228417,0.0002253896,0.0002498325,0.0004804681,0.00003726782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000770813,"about_ca_system_score_gemma":0.0003532055,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003630136,"about_ca_topic_score_gemma":0.0003260051,"domain_scores_codex":[0.9945286,0.0008477682,0.0007535053,0.0002841342,0.003304952,0.0002810369],"domain_scores_gemma":[0.9960555,0.001278764,0.000226574,0.0007778426,0.001565251,0.00009609371],"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":[0.0003067211,0.002660891,0.07062361,0.00004115764,0.0002490529,0.00001602876,0.02071112,0.801421,0.002192802,0.07068738,0.008798352,0.02229187],"study_design_scores_gemma":[0.003122207,0.003076831,0.1204311,0.00008816866,0.0002069384,0.0001001459,0.04475681,0.535891,0.02039692,0.2552597,0.01569325,0.000976933],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8230623,0.0001018436,0.1700144,0.0003399242,0.0000546059,0.0005576255,0.003151423,0.00001633073,0.002701507],"genre_scores_gemma":[0.9641448,0.0001937632,0.03474286,0.000001235367,0.00002337896,0.0000646925,0.00004015125,0.00001339231,0.0007756965],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.26553,"threshold_uncertainty_score":0.9987062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1947969292585974,"score_gpt":0.4235596820432506,"score_spread":0.2287627527846532,"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."}}