{"id":"W4307526278","doi":"10.32920/21408570.v1","title":"Performance Analysis of LSTMs for Daily Individual EV Charging Behavior Prediction","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Duration (music); Computer science; Term (time); Training set; Running time; Performance prediction; Artificial intelligence; Real-time computing; Simulation; Algorithm; Acoustics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.002093208,0.001306131,0.0007002692,0.0006375898,0.0003516641,0.000627895,0.0008553491,0.001166225,0.001739536],"category_scores_gemma":[0.005705981,0.0002857753,0.0004590184,0.0005837877,0.000314866,0.001483138,0.0005841021,0.001367953,0.0006104588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009277632,"about_ca_system_score_gemma":0.000896179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01504503,"about_ca_topic_score_gemma":0.01213808,"domain_scores_codex":[0.9993686,0.0001744752,0.00005445392,0.000155556,0.0001285507,0.0001183488],"domain_scores_gemma":[0.9981297,0.00122391,0.0001045493,0.0001337508,0.0003396358,0.00006846651],"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":[0.001083054,0.0003611417,0.01076541,0.0002853944,0.0002771968,0.0001877732,0.0001434483,0.6197681,0.01105798,0.0009541417,0.00455747,0.350559],"study_design_scores_gemma":[0.000005055776,0.0000667079,0.0008442199,0.000008647668,0.00001268412,0.0000161922,0.00002181354,0.9957058,0.002847767,0.0003104249,0.0001537409,0.000006912311],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8216385,0.005669799,0.1563894,0.001797274,0.0005938857,0.00007767714,0.001321632,0.005476649,0.007035228],"genre_scores_gemma":[0.9798906,0.0004349214,0.01707151,0.0001579256,0.00004463387,0.00003453488,0.0009123306,0.00005859563,0.001395121],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01504503,"threshold_uncertainty_score":0.02991498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01265079024333768,"score_gpt":0.2268166082554457,"score_spread":0.214165818012108,"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."}}