{"id":"W2090966031","doi":"10.1016/j.jmva.2014.12.004","title":"Construction and sampling of Archimedean and nested Archimedean Lévy copulas","year":2014,"lang":"en","type":"article","venue":"Journal of Multivariate Analysis","topic":"Probability and Risk Models","field":"Decision Sciences","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Mathematics; Lévy process; Sampling (signal processing); Class (philosophy); Copula (linguistics); Pure mathematics; Applied mathematics; Discrete mathematics; Econometrics; Computer science; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007232918,0.0005794755,0.001185393,0.002659765,0.0009032721,0.001890304,0.002395767,0.001083729,0.001826463],"category_scores_gemma":[0.03264136,0.001141122,0.001549975,0.001475422,0.001926628,0.001849081,0.002543472,0.002056591,0.0002219945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001301315,"about_ca_system_score_gemma":0.002066473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002293629,"about_ca_topic_score_gemma":0.002172041,"domain_scores_codex":[0.9973573,0.00119653,0.0001573147,0.0003758059,0.0006720325,0.0002409861],"domain_scores_gemma":[0.9841626,0.009309922,0.000829013,0.002237231,0.002399971,0.001061412],"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":[0.0001923273,0.0002477994,0.009514153,0.0001129326,0.00008859336,0.0004477985,0.0007271305,0.2035294,0.009662957,0.7243308,0.001603427,0.04954268],"study_design_scores_gemma":[0.00002045594,0.00004096113,0.0008836919,0.00001439867,0.00001369538,0.00008731584,0.00005043367,0.8732852,0.001286331,0.1235044,0.0007934878,0.00001978814],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06581634,0.0000724463,0.9328855,0.00008612093,0.00002821709,0.00009133771,0.00007085696,0.0001241217,0.0008250711],"genre_scores_gemma":[0.4967321,0.0001925219,0.5005595,0.0001042616,0.00006573583,0.0002574098,0.000532432,0.0001609594,0.001395095],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007232918,"threshold_uncertainty_score":0.03825182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09158237339767354,"score_gpt":0.3860671303866499,"score_spread":0.2944847569889764,"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."}}