{"id":"W4403052777","doi":"10.2139/ssrn.4974855","title":"Kolmogorov-Arnold Recurrent Network for Short Term Load Forecasting Across Diverse Consumers","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Term (time); Computer science; Economics; 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":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.002346659,0.0007541931,0.0006848044,0.0001267213,0.0004482263,0.0004015798,0.0006733492,0.0005275669,0.00001800872],"category_scores_gemma":[0.0000824388,0.0007499332,0.0006945923,0.0002147511,0.00007512331,0.0001178704,0.000600539,0.008090278,0.00001868902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003238594,"about_ca_system_score_gemma":0.001728549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003922261,"about_ca_topic_score_gemma":0.002569983,"domain_scores_codex":[0.9929073,0.00004680116,0.0008435483,0.00060212,0.0004545319,0.005145737],"domain_scores_gemma":[0.9988855,0.0001599595,0.0001807323,0.0003704838,0.0001665093,0.0002367865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000190774,0.00005607856,0.002827698,0.001496127,0.003871134,0.00008465924,0.00186224,0.2711145,0.0001540439,0.00831124,0.004770376,0.7052612],"study_design_scores_gemma":[0.002913724,0.001116799,0.0001907929,0.01043985,0.002168347,0.003958199,0.00373667,0.4859818,0.0005693637,0.4202861,0.06265947,0.00597896],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7896746,0.1261292,0.03928934,0.0001811019,0.03328114,0.001400769,0.0004914976,0.001524972,0.008027363],"genre_scores_gemma":[0.9837191,0.01006347,0.000949176,0.00001869014,0.00387638,0.00009838138,0.0001217752,0.0002772155,0.0008758601],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6992822,"threshold_uncertainty_score":0.9994951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02398838820127136,"score_gpt":0.2650017553918405,"score_spread":0.2410133671905691,"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."}}