{"id":"W4396629565","doi":"10.2139/ssrn.4816584","title":"Pareto Efficiency and Financial Fairness Under Limited Expected Loss Constraint","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"","keywords":"Pareto principle; Constraint (computer-aided design); Economics; Pareto optimal; Pareto efficiency; Microeconomics; Finance; Multi-objective optimization; Mathematical optimization; Mathematics; Operations management","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.005670503,0.0004738574,0.0006674902,0.0008600416,0.0003750666,0.001183587,0.0009808537,0.000545654,0.0001038558],"category_scores_gemma":[0.001190954,0.0003570053,0.0003267758,0.0009713447,0.000318529,0.0001609947,0.0007296196,0.005587643,0.0001072449],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007118778,"about_ca_system_score_gemma":0.00909129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006109956,"about_ca_topic_score_gemma":0.0005453514,"domain_scores_codex":[0.9936907,0.0003716942,0.001259052,0.0009976295,0.001542787,0.002138147],"domain_scores_gemma":[0.9975176,0.0003660721,0.0006779496,0.0005725172,0.0006300375,0.0002358448],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003311577,0.0003084896,0.005773718,0.00004296464,0.0004512247,0.0002689034,0.00365451,0.05265525,0.00007564397,0.6565838,0.0035438,0.2763105],"study_design_scores_gemma":[0.000454236,0.000168514,0.001181972,0.0001015001,0.0001007378,0.001103927,0.002713112,0.006316238,0.00002295674,0.9858391,0.001523976,0.0004737756],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6969039,0.01869817,0.2756522,0.002649922,0.003229281,0.0004842607,0.00005153249,0.000146251,0.002184457],"genre_scores_gemma":[0.9808252,0.01643733,0.0001814758,0.0001156968,0.0006581444,0.00001444168,0.00002097355,0.0000427531,0.001703931],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3292552,"threshold_uncertainty_score":0.9998882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03106901399878645,"score_gpt":0.3253062649164938,"score_spread":0.2942372509177074,"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."}}