{"id":"W2903241066","doi":"10.1002/cjs.11468","title":"Predictive assessment of copula models","year":2018,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Innovative Research Group Project of the National Natural Science Foundation of China","keywords":"Copula (linguistics); Bivariate analysis; Multivariate statistics; Predictive power; Econometrics; Quantile; Statistics; Model selection; Computer science; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007484722,0.0001023082,0.0003618546,0.000145845,0.00006922104,0.00002435479,0.0002111409,0.00005518215,0.0006723009],"category_scores_gemma":[0.002511687,0.00008578782,0.00004343954,0.0001159064,0.0003307235,0.00006306235,0.00001024617,0.0001922104,0.000002389079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001175784,"about_ca_system_score_gemma":0.001522523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005987148,"about_ca_topic_score_gemma":0.00204269,"domain_scores_codex":[0.9985688,0.0001299496,0.0007090875,0.00008409403,0.000288921,0.0002191172],"domain_scores_gemma":[0.9965804,0.0009496232,0.0005168862,0.0001696621,0.001315807,0.0004676807],"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":[0.000009042561,0.00002012183,0.001464095,0.00004128646,0.00005697091,0.00005464249,0.0004396714,0.00002450248,0.00002998431,0.9708803,0.0210414,0.005938027],"study_design_scores_gemma":[0.0002553822,0.0007522004,0.006438846,0.0001104364,0.00008312611,0.00003914383,0.0001710216,0.02437727,0.0001064067,0.9669735,0.0005969091,0.00009577859],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005973219,0.0000216192,0.9832237,0.00004803821,0.0003846553,0.00007121271,0.001245087,0.000002043098,0.009030405],"genre_scores_gemma":[0.444258,0.00000415014,0.5555496,0.00003508693,0.0000925623,5.056255e-7,0.00000133358,0.000009154496,0.00004957596],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4382848,"threshold_uncertainty_score":0.7361223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.136298318111266,"score_gpt":0.3868095029359923,"score_spread":0.2505111848247262,"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."}}