{"id":"W4405283472","doi":"10.1016/j.eng.2024.10.021","title":"LearningEMS: A Unified Framework and Open-Source Benchmark for Learning-Based Energy Management of Electric Vehicles","year":2024,"lang":"en","type":"article","venue":"Engineering","topic":"Electric and Hybrid Vehicle Technologies","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Natural Science Foundation of China","keywords":"Benchmark (surveying); Open source; Computer science; Energy management; Energy (signal processing); Systems engineering; Engineering; Automotive engineering; Geology; Operating system; 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":[0.0001579649,0.0001778098,0.0002140616,0.000262049,0.00004640614,0.00009319075,0.0002419791,0.0001048496,0.000006733336],"category_scores_gemma":[0.00003579094,0.0001898946,0.00004849352,0.0005644677,0.00001454662,0.00008823838,0.0000695311,0.0003013018,0.000001423138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004761347,"about_ca_system_score_gemma":0.00001028034,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008259414,"about_ca_topic_score_gemma":3.854049e-7,"domain_scores_codex":[0.9991956,0.000006736716,0.0001871902,0.0002144686,0.0000941684,0.0003018168],"domain_scores_gemma":[0.9995378,0.0002433827,0.00001822071,0.0001452498,0.00001565901,0.00003972504],"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":[0.00001482673,0.00001361869,0.000125991,0.001379479,0.0002491379,0.00001816639,0.00006887819,0.7849938,0.005208834,0.03807006,0.0004623836,0.1693948],"study_design_scores_gemma":[0.0001879707,0.000113164,0.000328092,0.0003876664,0.00004335287,0.000003802428,0.00002620595,0.9337988,0.02191833,0.0005613349,0.04239107,0.000240234],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1302876,0.01527102,0.8513897,0.00006567487,0.0001278648,0.0002421408,0.000002046483,0.002108335,0.0005056529],"genre_scores_gemma":[0.9874997,0.0007206895,0.01129449,0.000006694979,0.00003713214,0.00009900406,0.000005848828,0.00007347479,0.0002630233],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8572121,"threshold_uncertainty_score":0.7743677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006573402790559575,"score_gpt":0.2100230740934693,"score_spread":0.2034496713029098,"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."}}