{"id":"W4413122761","doi":"10.3390/info16080676","title":"An Approximate Algorithm for Sparse Distributionally Robust Optimization","year":2025,"lang":"en","type":"article","venue":"Information","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta","keywords":"Robust optimization; Computer science; Algorithm; Mathematical optimization; Optimization algorithm; Mathematics","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":[0.001334945,0.0007697697,0.001234847,0.000584874,0.0003738607,0.0009901328,0.001240141,0.001280312,0.003555024],"category_scores_gemma":[0.004075456,0.0004553372,0.0006715533,0.0007648166,0.000765483,0.001308179,0.001572461,0.001805164,0.0008623649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007797189,"about_ca_system_score_gemma":0.001225391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002151561,"about_ca_topic_score_gemma":0.002068395,"domain_scores_codex":[0.9993281,0.0002354501,0.00003401651,0.0001144619,0.0002291386,0.0000587905],"domain_scores_gemma":[0.998798,0.0007151257,0.0001080912,0.00015863,0.0001726942,0.00004751074],"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":[0.00006347221,0.00004761925,0.0003166859,0.00006877678,0.00003645726,0.00004942674,0.00004361312,0.8425561,0.001947444,0.05904265,0.001978887,0.09384888],"study_design_scores_gemma":[0.000006111236,0.0000106021,0.00001446554,0.000002483135,0.000001675691,0.0000103626,0.000002434879,0.9927671,0.0001670316,0.006669935,0.0003456743,0.000002160441],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001150986,0.00004959779,0.9980646,0.00005821369,0.0000114263,0.00001475798,0.00001142253,0.0001022883,0.0005367228],"genre_scores_gemma":[0.194515,0.000233046,0.8013037,0.0002028899,0.00008447325,0.0002310504,0.0001878698,0.0001595855,0.00308232],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003555024,"threshold_uncertainty_score":0.01189274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04056409178548765,"score_gpt":0.3444525310708437,"score_spread":0.303888439285356,"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."}}