{"id":"W3215731291","doi":"10.1109/epec52095.2021.9621740","title":"Electric Vehicles Load Forecasting Considering the Effect of COVID-19 Pandemic","year":2021,"lang":"en","type":"article","venue":"","topic":"Electric Vehicles and Infrastructure","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; Kalman filter; Computer science; Electric vehicle; Extended Kalman filter; Automotive engineering; Engineering; Artificial intelligence; Medicine; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0006113152,0.0004282286,0.0004171358,0.000310953,0.0002310535,0.0007701387,0.0004129921,0.0007269314,0.0006695725],"category_scores_gemma":[0.001928476,0.0001885907,0.0003629769,0.0004222653,0.0001600701,0.00111113,0.0003610061,0.0005854669,0.0001146428],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004810761,"about_ca_system_score_gemma":0.0006371199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02878134,"about_ca_topic_score_gemma":0.01621685,"domain_scores_codex":[0.9997727,0.00005172728,0.00001305148,0.00007063844,0.00004405441,0.0000476519],"domain_scores_gemma":[0.9994821,0.0002650532,0.0000760999,0.00002466494,0.0001283183,0.00002378564],"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":[0.0001073393,0.000042784,0.02252524,0.00005581267,0.00005012022,0.0003569899,0.00005969181,0.9521095,0.002007013,0.002377627,0.0009113701,0.01939659],"study_design_scores_gemma":[0.000002156582,0.0000174991,0.003923688,0.000002953475,0.00001155388,0.00001665047,0.00004230066,0.9950073,0.0003113013,0.0004532773,0.0002045446,0.000006731421],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8323771,0.0006290518,0.1568985,0.001215494,0.0002288219,0.00004706012,0.0005529702,0.0002631505,0.007787865],"genre_scores_gemma":[0.9953986,0.0002035178,0.003123915,0.00002569432,0.00004408174,0.000006514198,0.0001767737,0.000009568413,0.001011438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02878134,"threshold_uncertainty_score":0.05722767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01626514887722758,"score_gpt":0.2309862624817246,"score_spread":0.2147211136044971,"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."}}