{"id":"W4213203740","doi":"10.1002/9780470057339.vnn079","title":"Copulas and Copula Models","year":2012,"lang":"en","type":"other","venue":"Encyclopedia of Environmetrics","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Copula (linguistics); Econometrics; Computer science; Mathematics","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003693912,0.0003191651,0.000838512,0.0009092336,0.00003896522,0.00001267797,0.0002351659,0.0005484457,0.001398075],"category_scores_gemma":[0.0001741186,0.0003869235,0.0001301014,0.0003604276,0.0001312451,0.0001340052,0.0001474019,0.0002833855,0.0003342148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004814584,"about_ca_system_score_gemma":0.00001259484,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008186699,"about_ca_topic_score_gemma":0.00002237277,"domain_scores_codex":[0.9983378,0.00001418585,0.0007081952,0.0004907579,0.00008281371,0.000366251],"domain_scores_gemma":[0.998573,0.00006855752,0.0006940729,0.0005144342,0.000006181747,0.0001437378],"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":[0.00002868872,0.0006818507,0.2323218,0.0009790877,0.0002539321,0.000008698456,0.0009560865,0.000389745,0.000001787372,0.3796348,0.3403871,0.04435654],"study_design_scores_gemma":[0.0002495366,0.00003253254,0.003451886,0.0000379552,0.00002627802,0.000001092749,0.000008837936,0.001513658,9.819327e-7,0.01531815,0.9789349,0.0004241681],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.001041363,0.08506588,0.0151879,0.00001911318,0.000687625,0.0002733524,0.0005781649,0.0000522495,0.8970944],"genre_scores_gemma":[0.05019718,0.1566901,0.01826701,0.00007245159,0.000962952,0.0000320865,0.0001376973,0.0008614236,0.772779],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.6385478,"threshold_uncertainty_score":0.9998583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02864304021616914,"score_gpt":0.2012687906610845,"score_spread":0.1726257504449154,"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."}}