{"id":"W4402848471","doi":"10.21105/joss.06744","title":"LocalCop: An R package for local likelihood inferencefor conditional copulas","year":2024,"lang":"en","type":"article","venue":"The Journal of Open Source Software","topic":"Financial Risk and Volatility Modeling","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"R package; Inference; Econometrics; Copula (linguistics); Mathematics; Computer science; Statistics; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002017096,0.0001489886,0.0004072606,0.0001366466,0.0002474538,0.0003641114,0.0008393256,0.0000986336,0.0002710706],"category_scores_gemma":[0.0002804844,0.0001159383,0.0001870369,0.00018039,0.0001059345,0.0007977693,0.000135638,0.0003426443,0.0001132669],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000105519,"about_ca_system_score_gemma":0.0001605361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001647928,"about_ca_topic_score_gemma":0.00004200281,"domain_scores_codex":[0.9986365,0.00003430273,0.0007888135,0.0001921466,0.00007928799,0.0002688763],"domain_scores_gemma":[0.9988611,0.0002973926,0.0003297752,0.0002484255,0.0001427743,0.0001204856],"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":[0.002478712,0.001146829,0.05963087,0.0008885359,0.00114378,0.00008029611,0.02294813,0.05022447,0.00009005509,0.410865,0.06816703,0.3823363],"study_design_scores_gemma":[0.001394922,0.001011645,0.005708265,0.0002863853,0.00008087629,0.0001220305,0.00120588,0.07164805,0.0001316588,0.7426326,0.1753066,0.0004711315],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1158611,0.002652912,0.8797638,0.00052843,0.0003966908,0.0002716076,0.0003101462,0.00002631953,0.0001890346],"genre_scores_gemma":[0.9944071,0.00009610977,0.004372956,0.0003129142,0.0003852722,0.0000102169,0.0000353368,0.00003786319,0.0003422394],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.878546,"threshold_uncertainty_score":0.4727827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05948773611913625,"score_gpt":0.3033217623662094,"score_spread":0.2438340262470731,"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."}}