{"id":"W3195205837","doi":"10.5539/ijsp.v10n5p20","title":"Fitting Compound Archimedean Copulas to Data for Modeling Electricity Demand","year":2021,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Copula (linguistics); Mathematics; Econometrics; Tail dependence; Statistical physics; Mathematical optimization; Statistics; Physics; Multivariate statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006531506,0.00173538,0.001707022,0.002076501,0.0006151869,0.001610124,0.001885211,0.001891539,0.002267019],"category_scores_gemma":[0.02274226,0.0009862803,0.00230016,0.003193975,0.0008075632,0.002678062,0.001162855,0.003197149,0.0009592862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001265123,"about_ca_system_score_gemma":0.001521535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00634002,"about_ca_topic_score_gemma":0.006041463,"domain_scores_codex":[0.9977635,0.001282803,0.0001209843,0.0003988124,0.0002835927,0.0001503882],"domain_scores_gemma":[0.9894554,0.00757886,0.0009797573,0.001138676,0.0006964918,0.0001508732],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005734004,0.00007490678,0.006116612,0.0001338005,0.0001994364,0.0002204795,0.0001245059,0.933149,0.001254698,0.02973655,0.001599456,0.02733327],"study_design_scores_gemma":[0.000003405298,0.00002011521,0.0007597001,0.000008975932,0.00000817328,0.00003718154,0.00001664237,0.9892412,0.000280787,0.009116175,0.0004964745,0.00001121603],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04892335,0.0003554917,0.9485155,0.0002379202,0.0000598014,0.0001100929,0.0005733663,0.000279266,0.0009450783],"genre_scores_gemma":[0.6484811,0.001415447,0.3436916,0.0002434657,0.0001890477,0.0006292266,0.002165537,0.0003151377,0.002869455],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006531506,"threshold_uncertainty_score":0.03454232,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04207752067156798,"score_gpt":0.2918518358083031,"score_spread":0.2497743151367351,"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."}}