{"id":"W3092314949","doi":"10.3390/risks8040103","title":"Grouped Normal Variance Mixtures","year":2020,"lang":"en","type":"article","venue":"Risks","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Copula (linguistics); Mathematics; Multivariate normal distribution; Multivariate statistics; Variance (accounting); Monte Carlo method; Statistics; Mixing (physics); Multivariate t-distribution; Applied mathematics; Econometrics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005423149,0.001705629,0.001999951,0.002749001,0.001048194,0.003899843,0.003297018,0.001985459,0.01960671],"category_scores_gemma":[0.02286839,0.0009673776,0.00342944,0.003050293,0.001792104,0.004274276,0.003097576,0.002767347,0.005864574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001607434,"about_ca_system_score_gemma":0.001754908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006226336,"about_ca_topic_score_gemma":0.006756587,"domain_scores_codex":[0.995408,0.001933573,0.0002118847,0.001154365,0.0009755671,0.0003166478],"domain_scores_gemma":[0.9947285,0.002505729,0.0005240628,0.001069627,0.0009926023,0.000179486],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003334695,0.0001451643,0.005981164,0.0003171801,0.0003792718,0.0003656904,0.0006177579,0.2499264,0.003190351,0.4805719,0.01767084,0.2405009],"study_design_scores_gemma":[0.0000326206,0.00005952685,0.001563875,0.0001047977,0.00006087721,0.0002432948,0.0001277293,0.6712492,0.001516574,0.3025133,0.02244513,0.00008305152],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003759587,0.0002008779,0.992935,0.000110648,0.00007897621,0.00009796359,0.0003978639,0.0006175538,0.001801508],"genre_scores_gemma":[0.2044435,0.000926808,0.7696759,0.0003949916,0.000345825,0.0008364752,0.003817134,0.001322994,0.01823632],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01960671,"threshold_uncertainty_score":0.06559098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1129438916127381,"score_gpt":0.2579721307069157,"score_spread":0.1450282390941776,"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."}}