{"id":"W3200210278","doi":"10.1109/tte.2021.3111966","title":"Machine Learning-Based Vehicle Model Construction and Validation—Toward Optimal Control Strategy Development for Plug-In Hybrid Electric Vehicles","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Transportation Electrification","topic":"Electric and Hybrid Vehicle Technologies","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"H2020 Marie Skłodowska-Curie Actions; National Key Research and Development Program of China; Engineering and Physical Sciences Research Council; Queen's University; National Natural Science Foundation of China; Queen's University Belfast","keywords":"Plug-in; Computer science; Benchmark (surveying); Electric vehicle; Process (computing); Powertrain; Test bench; Automotive engineering; Control engineering; Engineering; Torque; Embedded system; Power (physics)","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":[0.001050523,0.000535957,0.0005063926,0.0003956242,0.0003017463,0.0005824671,0.0006738771,0.0004908092,0.0009144473],"category_scores_gemma":[0.002382359,0.0003036388,0.0004492244,0.0002056144,0.0004584051,0.0004890908,0.0005712487,0.0008238244,0.0001543104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005399985,"about_ca_system_score_gemma":0.001143095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006482278,"about_ca_topic_score_gemma":0.003366744,"domain_scores_codex":[0.9996555,0.0001315756,0.0000190493,0.00004097611,0.000121511,0.00003138456],"domain_scores_gemma":[0.9992989,0.0002969223,0.00008358376,0.00007788486,0.000226074,0.00001652581],"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":[0.00001173287,0.00001232252,0.0002818551,0.00002618729,0.000007396884,0.00001718807,0.00001334482,0.985817,0.001005485,0.002678242,0.0001228813,0.01000636],"study_design_scores_gemma":[0.000001251419,0.000009375654,0.00004586082,0.000002289407,8.606903e-7,0.000002411546,0.000002611002,0.9989395,0.0003740379,0.0004700198,0.0001504015,0.00000135012],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02323038,0.00009725536,0.9739721,0.00008589363,0.00002177316,0.00005693619,0.00004378595,0.0003061258,0.002185887],"genre_scores_gemma":[0.893604,0.0001221153,0.1046559,0.00004162878,0.00001226706,0.0002175592,0.0001536424,0.00005329615,0.001139602],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006482278,"threshold_uncertainty_score":0.01288909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01429037681502924,"score_gpt":0.2161865887689426,"score_spread":0.2018962119539133,"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."}}