{"id":"W4293223634","doi":"10.11159/eee22.102","title":"Electric Load Estimation and Prediction Using Periodic Steady State Kalman Filter","year":2022,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Kalman filter; Control theory (sociology); Moving horizon estimation; Extended Kalman filter; Computer science; Steady state (chemistry); Fast Kalman filter; Estimation; State (computer science); Invariant extended Kalman filter; Artificial intelligence; Engineering; Algorithm","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000337482,0.0001352554,0.0001641852,0.0002493402,0.0003055628,0.0001687145,0.0001609592,0.00001673172,4.475019e-7],"category_scores_gemma":[0.00001429953,0.0001108145,0.00001826821,0.0008099352,0.00005346145,0.0001835639,0.0001088854,0.0002219995,4.843539e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009495543,"about_ca_system_score_gemma":0.00001994574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001419948,"about_ca_topic_score_gemma":3.674132e-7,"domain_scores_codex":[0.998992,0.00000503887,0.0001967974,0.0002237987,0.0003298615,0.0002524551],"domain_scores_gemma":[0.9997153,0.00003728668,0.00005856469,0.0000561175,0.00005539336,0.00007732739],"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":[0.00001583092,0.00001887114,0.002269647,0.0002817011,0.00002892482,0.000001240048,0.0006239382,0.949388,0.02692574,0.004142627,0.0001563965,0.01614707],"study_design_scores_gemma":[0.0001403149,0.000100903,0.001344379,0.0001089987,0.000008896534,0.00007495059,0.000009553908,0.9964629,0.001253601,0.00001611154,0.0003611257,0.000118298],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966732,0.0008713315,0.00125995,0.00001755311,0.0008286683,0.0001307115,0.000003103798,0.00009759782,0.0001179224],"genre_scores_gemma":[0.9995113,0.00002198374,0.0002909043,0.000009857959,0.0000572155,0.00001382853,1.80562e-7,0.00001203412,0.00008272311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04707485,"threshold_uncertainty_score":0.4518883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007794277202114484,"score_gpt":0.1899927562338874,"score_spread":0.182198479031773,"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."}}