{"id":"W4396768245","doi":"10.23977/jeeem.2024.070115","title":"Urban Electricity Consumption Forecasting Based on SARIMA and Random Forest Modeling","year":2024,"lang":"en","type":"article","venue":"Journal of Electrotechnology Electrical Engineering and Management","topic":"Evaluation Methods in Various Fields","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Electricity; Consumption (sociology); Random forest; Environmental science; Computer science; Engineering; Artificial intelligence; Electrical engineering","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":[0.001036448,0.0001503065,0.0002103465,0.0004141666,0.00007476411,0.00004737643,0.0001183962,0.0001289484,0.00001644439],"category_scores_gemma":[0.0002365938,0.0001309394,0.00005268599,0.0004257082,0.00003513651,0.00008875804,0.00005031622,0.0006742773,0.000003009158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001923033,"about_ca_system_score_gemma":0.00001003606,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004756427,"about_ca_topic_score_gemma":0.000001402451,"domain_scores_codex":[0.998846,0.00004674695,0.0003192516,0.0002288822,0.0002564432,0.0003026994],"domain_scores_gemma":[0.9995194,0.0002356471,0.00006721987,0.0001012887,0.00001197682,0.00006448007],"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":[0.0002669701,0.00009352217,0.001523143,0.0002017402,0.0001830148,0.0002075636,0.00004752819,0.7815651,0.009402038,0.01873651,0.001079791,0.186693],"study_design_scores_gemma":[0.0005963415,0.0005478686,0.0002030005,0.00006617002,0.00008066648,0.0001436968,0.000001353147,0.994126,0.0008416358,0.002211665,0.001056041,0.000125583],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1673313,0.001197298,0.8301764,0.0006339796,0.00008070737,0.0002072288,1.704816e-7,0.0001013551,0.0002715701],"genre_scores_gemma":[0.9649487,0.0007232855,0.03411153,0.0001138076,0.00003572768,0.00001363593,3.542071e-7,0.0000177493,0.0000351999],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7976174,"threshold_uncertainty_score":0.5339555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01742188322002824,"score_gpt":0.2500048113641465,"score_spread":0.2325829281441182,"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."}}