{"id":"W1986305797","doi":"10.1016/j.jmva.2013.08.018","title":"Geometric interpretation of the residual dependence coefficient","year":2013,"lang":"en","type":"article","venue":"Journal of Multivariate Analysis","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Residual; Weibull distribution; Interpretation (philosophy); Independence (probability theory); Computation; Statistics; Measure (data warehouse); Statistical physics; Physics","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":[0.001032764,0.00008512683,0.00046921,0.0008618185,0.00006452445,0.00004082333,0.0003353205,0.00006488162,0.0001809079],"category_scores_gemma":[0.0009202921,0.00006392804,0.0004484214,0.001809007,0.00003469772,0.0002632156,0.00005712055,0.0001837213,0.0000250792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006712154,"about_ca_system_score_gemma":0.00002885385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001483813,"about_ca_topic_score_gemma":0.00004128654,"domain_scores_codex":[0.9984543,0.00004139209,0.001119714,0.0001373593,0.0001132768,0.0001339497],"domain_scores_gemma":[0.9978243,0.0001313407,0.001465181,0.0002337509,0.0003008821,0.00004456678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009371524,0.0004301612,0.582772,0.00003858704,0.002025488,0.000002336015,0.003488977,0.3900535,0.0007416676,0.008486683,0.0003344282,0.01153245],"study_design_scores_gemma":[0.0002682534,0.00004722726,0.5208261,0.00001831967,0.0001902843,0.000001291634,0.00009439645,0.4746894,0.0003121376,0.003359218,0.0001130543,0.00008033924],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7536821,0.0006340137,0.2448578,0.0002487124,0.000171895,0.00006758792,0.00001079103,0.000002161836,0.0003248738],"genre_scores_gemma":[0.9977882,0.0000700905,0.001946003,0.00003650383,0.00004377708,0.000001388751,8.625601e-7,0.000005700881,0.0001074973],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.244106,"threshold_uncertainty_score":0.260691,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02199314596964882,"score_gpt":0.241756553106266,"score_spread":0.2197634071366171,"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."}}