{"id":"W2578066853","doi":"","title":"CHOICE OF PARAMETRIC FAMILIES OF COPULAS","year":2008,"lang":"en","type":"article","venue":"","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Copula (linguistics); Nonparametric statistics; Mathematics; Parametric statistics; Hellinger distance; Econometrics; Smoothing; Statistics","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":[0.0001673294,0.00007111944,0.00036434,0.0002773369,0.00003569021,0.000002148445,0.0001248016,0.00006365083,0.0001358903],"category_scores_gemma":[0.0003552473,0.00007834475,0.0001013722,0.0004639303,0.00007966043,0.00009392971,0.00002850404,0.00006574552,0.00005146689],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000147488,"about_ca_system_score_gemma":0.00001739858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003502732,"about_ca_topic_score_gemma":0.00004431922,"domain_scores_codex":[0.9990703,0.000004208774,0.0006058662,0.0001638452,0.00003030951,0.0001254807],"domain_scores_gemma":[0.9993804,0.00008758748,0.0002381485,0.0002218406,0.00004516909,0.00002688303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009023396,0.00009158905,0.9048343,0.00003785436,0.0000129018,3.591541e-7,0.0002535924,0.000374529,0.00002943417,0.09330367,0.000282673,0.0007700909],"study_design_scores_gemma":[0.0006700253,0.0001630675,0.9335322,0.00001648378,0.00000517477,0.000001687109,0.00007898721,0.02899364,0.002663407,0.02145766,0.01215871,0.0002588879],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9637086,0.001418315,0.007232865,0.00002442982,0.0001040868,0.0000691788,0.0000350216,0.00001309954,0.02739437],"genre_scores_gemma":[0.9958897,0.0007354268,0.002727504,0.00002292393,0.00002069472,0.000002240605,0.000002524107,0.000007239285,0.0005917651],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.071846,"threshold_uncertainty_score":0.5295106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09391300346303681,"score_gpt":0.2467817465711315,"score_spread":0.1528687431080947,"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."}}