{"id":"W4407970704","doi":"10.1007/s12273-025-1236-8","title":"ResiDualNet: A novel electric vehicle charging data imputation technique to enhance load forecasting accuracy","year":2025,"lang":"en","type":"article","venue":"Building Simulation","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Imputation (statistics); Electric vehicle; Automotive engineering; Computer science; Reliability engineering; Data mining; Engineering; Machine learning; Missing data; 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":[],"consensus_categories":[],"category_scores_codex":[0.0003532449,0.0001706834,0.0001528427,0.0002686948,0.0001512735,0.00009538858,0.0003083235,0.0001147746,0.000006992042],"category_scores_gemma":[0.0005524971,0.0001911755,0.0000255717,0.001246045,0.000004618521,0.0005768319,0.00009683408,0.0002328113,0.000004248461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003147286,"about_ca_system_score_gemma":0.00006841051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003210184,"about_ca_topic_score_gemma":0.000006401581,"domain_scores_codex":[0.9987965,0.00001592655,0.000318254,0.0003436999,0.0001965406,0.0003290839],"domain_scores_gemma":[0.9991102,0.0002733127,0.00006429714,0.0003984665,0.0001079098,0.00004577306],"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":[0.000008642737,0.000003945358,0.00007790967,0.00004234812,0.00001216603,5.125798e-7,0.00006531808,0.6005628,0.2887624,0.0003133707,0.0002210439,0.1099295],"study_design_scores_gemma":[0.0001368174,0.00001842529,0.0009069272,0.0001296029,0.00001475638,0.00000201807,0.000006982157,0.8788428,0.1167502,0.001291335,0.001729573,0.0001705683],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3043766,0.0002154869,0.6941947,0.00007621821,0.00009696972,0.0003952877,0.000007267641,0.0003292041,0.000308289],"genre_scores_gemma":[0.9691483,0.000008101945,0.03048423,0.00009880769,0.0001351968,0.0000281083,0.00003140146,0.00003240471,0.00003343178],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6647717,"threshold_uncertainty_score":0.7795911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0187464286883978,"score_gpt":0.304786943941407,"score_spread":0.2860405152530092,"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."}}