{"id":"W3155825668","doi":"","title":"Moment Problem and Its Application to Tail Risk Assessment","year":2016,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Risk and Portfolio Optimization","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Fredericton; University of New Brunswick; University of Manitoba","funders":"","keywords":"Moment (physics); Mathematics; Semidefinite programming; Random variable; Numerical analysis; Applied mathematics; Second moment of area; Moment-generating function; Upper and lower bounds; Variable (mathematics); Matching (statistics); Function (biology); Linear programming; Mathematical optimization; Combinatorics; Mathematical analysis; Statistics; Physics; Geometry","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":[],"consensus_categories":[],"category_scores_codex":[0.005936195,0.0001122821,0.000150782,0.0002203746,0.0002541532,0.0001485192,0.0003207927,0.00004949232,0.00004972958],"category_scores_gemma":[0.0001761327,0.00006262494,0.00004940909,0.0003768606,0.00001572131,0.0003934991,0.00005949587,0.0003652149,0.0001853876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004700724,"about_ca_system_score_gemma":0.0007310191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001373314,"about_ca_topic_score_gemma":0.0001450689,"domain_scores_codex":[0.9973223,0.0001592687,0.0004604152,0.0003145438,0.0007911712,0.000952284],"domain_scores_gemma":[0.9988377,0.0001305533,0.0003449066,0.0002165045,0.0003043539,0.000166002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002830641,0.00003708027,0.01814135,3.661098e-7,0.00002852882,4.508532e-7,0.0001010299,0.0006494217,0.001630695,0.1274041,0.0006076057,0.8513711],"study_design_scores_gemma":[0.0008270906,0.0005094141,0.01121299,0.00001341311,0.00002734521,0.0001160943,0.0004234415,0.002047499,0.0004103594,0.9180119,0.06617525,0.0002252095],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1840764,0.0006013571,0.806728,0.006325081,0.00008601878,0.0003372885,0.000005142,0.00002021093,0.001820454],"genre_scores_gemma":[0.9794037,0.01420828,0.001332113,0.00008007484,0.0001398364,0.00002794715,7.127684e-7,0.00001093252,0.004796371],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8511459,"threshold_uncertainty_score":0.2553771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01733980684808953,"score_gpt":0.3351083047700109,"score_spread":0.3177684979219214,"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."}}