{"id":"W1528472061","doi":"10.58079/ou99","title":"Dynamic dependence ordering for Archimedean copulas and distorted copulas","year":2008,"lang":"en","type":"preprint","venue":"OpenEdition (OpenEdition)","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Centre National de la Recherche Scientifique; AXA Research Fund","keywords":"Copula (linguistics); Statistical physics; Tail dependence; Econometrics; Mathematics; Economics; Applied mathematics; Mathematical economics; Statistics; Physics; Multivariate statistics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.001470078,0.0006983075,0.0008495369,0.0004898913,0.002396973,0.0006546142,0.001135514,0.0005614464,0.0004427166],"category_scores_gemma":[0.0003827558,0.0008233557,0.0003884204,0.0004531087,0.001101893,0.003786175,0.0007960952,0.0007638108,0.000125285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005818942,"about_ca_system_score_gemma":0.0004674076,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002938182,"about_ca_topic_score_gemma":0.05225649,"domain_scores_codex":[0.9945281,0.0004850944,0.001004697,0.001539915,0.001463579,0.0009785782],"domain_scores_gemma":[0.9970071,0.0002921244,0.000807387,0.0008866311,0.0005566226,0.000450123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001236921,0.002814518,0.02863201,0.004657637,0.002541519,0.0007230833,0.01176463,0.007407445,0.0002381852,0.7709478,0.07328801,0.09574827],"study_design_scores_gemma":[0.00469551,0.0004794717,0.3837262,0.001983701,0.0009597883,0.00006042821,0.003713993,0.005654439,0.0001650769,0.08052482,0.5130461,0.004990509],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5495737,0.006440635,0.109813,0.06379928,0.0425917,0.03551234,0.009513302,0.003293315,0.1794628],"genre_scores_gemma":[0.975145,0.006417979,0.006467672,0.003205142,0.0008420387,0.002297358,0.003477338,0.0001114292,0.002036078],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.690423,"threshold_uncertainty_score":0.9994217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02609223476198364,"score_gpt":0.3020796037441982,"score_spread":0.2759873689822145,"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."}}