{"id":"W4400276706","doi":"10.1109/icsmartgrid61824.2024.10578263","title":"Campus Electric Load Forecasting Using Recurrent Neural Networks","year":2024,"lang":"en","type":"article","venue":"","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Artificial neural network; Computer science; Recurrent neural network; Electrical load; Artificial intelligence; Electrical engineering; Engineering; Voltage","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002805502,0.0003941856,0.0003598502,0.0005204485,0.0001718604,0.000618757,0.0004284853,0.0002879337,0.001217234],"category_scores_gemma":[0.001140323,0.0001559437,0.0002629238,0.00060553,0.00008257563,0.0006309863,0.0002357091,0.0003979621,0.0006226348],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000559827,"about_ca_system_score_gemma":0.0003607989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03940107,"about_ca_topic_score_gemma":0.04800309,"domain_scores_codex":[0.9998378,0.00002466548,0.000009675166,0.00003975502,0.0000650943,0.00002307828],"domain_scores_gemma":[0.9997218,0.000083149,0.00004831208,0.00002531335,0.0001110259,0.00001029834],"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":[0.0001577555,0.0001057693,0.01158327,0.00006091046,0.00007668542,0.0001398933,0.00005144401,0.8249475,0.005307915,0.000812083,0.004480655,0.1522761],"study_design_scores_gemma":[0.000001553577,0.000008067816,0.001694697,0.000002479049,0.000004126717,0.000006323292,0.00000724987,0.9970813,0.0007619248,0.0001751333,0.0002536347,0.00000346624],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7587411,0.0008377351,0.2174132,0.0006623369,0.0001454885,0.0000579323,0.002171034,0.00527623,0.0146949],"genre_scores_gemma":[0.9817781,0.0001838707,0.01352958,0.00002358864,0.00001955722,0.00001344295,0.001267763,0.00004979918,0.003134268],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03940107,"threshold_uncertainty_score":0.07834351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02171692908841549,"score_gpt":0.2283047402310211,"score_spread":0.2065878111426056,"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."}}