{"id":"W2121864813","doi":"10.1239/jap/1395771412","title":"Relations Between Hidden Regular Variation and the Tail Order of Copulas","year":2014,"lang":"en","type":"article","venue":"Journal of Applied Probability","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Division of Civil, Mechanical and Manufacturing Innovation; Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Mathematics; Copula (linguistics); Exponent; Univariate; Statistical physics; Multivariate random variable; Gaussian; Random variable; Mathematical analysis; Multivariate statistics; Statistics; Econometrics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00402639,0.00007788364,0.0004306881,0.00007062892,0.00009466578,0.00002232038,0.0001372975,0.00009192732,0.00002733282],"category_scores_gemma":[0.000675988,0.00006176587,0.00008486072,0.0001704569,0.0001370696,0.0001177274,0.0000360649,0.0002278785,0.000006512524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004639783,"about_ca_system_score_gemma":0.00003525843,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007108232,"about_ca_topic_score_gemma":0.000008589769,"domain_scores_codex":[0.9986637,0.00003912789,0.0009941194,0.0001424787,0.00006077237,0.00009976995],"domain_scores_gemma":[0.998404,0.0002610134,0.0009340037,0.0002261341,0.0001361415,0.00003867597],"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":[0.0001847712,0.00005104961,0.1542395,0.00004779166,0.00004728063,3.958761e-8,0.001733992,0.0007935914,0.00001854923,0.8386889,0.00005892817,0.004135665],"study_design_scores_gemma":[0.0008692901,0.00003714148,0.2091151,0.000008245199,0.00002104928,5.223849e-7,0.00001602908,0.005359959,0.00002729977,0.7832851,0.001203592,0.00005669548],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9249594,0.0002527218,0.0698365,0.0009302108,0.00008078237,0.0002272539,0.00001190415,0.00000475657,0.003696498],"genre_scores_gemma":[0.9869271,0.00002232546,0.01287179,0.00002545688,0.000120347,0.000003821088,0.000001458208,0.000006497757,0.00002118206],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06196775,"threshold_uncertainty_score":0.2518739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0227025971147108,"score_gpt":0.2050503605232608,"score_spread":0.18234776340855,"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."}}