{"id":"W3040195493","doi":"10.1017/asb.2020.21","title":"A STATISTICAL METHODOLOGY FOR ASSESSING THE MAXIMAL STRENGTH OF TAIL DEPENDENCE","year":2020,"lang":"en","type":"article","venue":"Astin Bulletin","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Western University","funders":"","keywords":"Estimator; Econometrics; Statistical inference; Tail dependence; Inference; Mathematics; Index (typography); Statistics; Diagonal; Statistical physics; Economics; Computer science; Physics","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":[0.001038505,0.0001006072,0.0003373336,0.00002966435,0.0001006278,0.00003232791,0.0002199346,0.0000738998,0.0004403428],"category_scores_gemma":[0.003738812,0.00009355499,0.00007811539,0.00009294308,0.00008802294,0.00003331523,0.00006897366,0.000165488,0.00008014729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000135678,"about_ca_system_score_gemma":0.00002886035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001898867,"about_ca_topic_score_gemma":0.000006136923,"domain_scores_codex":[0.9988459,0.00005436187,0.0005313664,0.0003062707,0.00003493926,0.0002271229],"domain_scores_gemma":[0.9983275,0.00119012,0.0002356458,0.0001482793,0.00004397655,0.00005448541],"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":[0.0002120968,0.0001034564,0.07647911,0.0002171923,0.00006009745,0.000005332207,0.00177364,0.0009016122,0.0002759147,0.8690474,0.008656,0.04226817],"study_design_scores_gemma":[0.00243326,0.0007425947,0.1117366,0.00007229001,0.00006899062,0.000009492526,0.001273345,0.3389312,0.001220417,0.1513768,0.3912334,0.0009016355],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1110943,0.0004927388,0.8807619,0.005903736,0.0001217883,0.0001837324,0.0002147674,0.00001850879,0.001208565],"genre_scores_gemma":[0.8262377,0.000016708,0.1731784,0.0003813604,0.0001039753,0.00001789778,0.000008861993,0.00001306055,0.00004209817],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7176706,"threshold_uncertainty_score":0.4821445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1493588403631138,"score_gpt":0.3113010884789929,"score_spread":0.1619422481158791,"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."}}