{"id":"W4393934500","doi":"10.3390/wevj15040149","title":"Application of Real-Life On-Road Driving Data for Simulating the Electrification of Long-Haul Transport Trucks","year":2024,"lang":"en","type":"article","venue":"World Electric Vehicle Journal","topic":"Electric and Hybrid Vehicle Technologies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; National Research Council Canada","funders":"Natural Resources Canada; Environment and Climate Change Canada","keywords":"Truck; Electrification; Automotive engineering; Transport engineering; Road transport; Environmental science; Computer science; Engineering; Electrical engineering; Electricity","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008886238,0.0001830118,0.0002943925,0.0004768542,0.0001512294,0.00004046908,0.0007355907,0.00008345592,0.000007228168],"category_scores_gemma":[0.0001155505,0.0001454036,0.0001178136,0.001698268,0.00003888399,0.0002140997,0.00001322981,0.0006497176,0.000002713677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001157092,"about_ca_system_score_gemma":0.0001250516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002346058,"about_ca_topic_score_gemma":0.00004015912,"domain_scores_codex":[0.9983188,0.00003051276,0.0007018272,0.0002516512,0.0003174848,0.0003797396],"domain_scores_gemma":[0.9986127,0.000464675,0.0001838433,0.0005769688,0.0001038613,0.00005797073],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009232628,0.0000785778,0.008194259,0.0003060924,0.0003291432,0.000007217207,0.0001128361,0.03553327,0.1032925,0.00517163,0.001337988,0.8455441],"study_design_scores_gemma":[0.0002978187,0.0001812018,0.02554753,0.0001007158,0.0001264409,0.00003433416,0.00001760523,0.9334531,0.03828764,0.001012444,0.0007603522,0.0001808406],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.800658,0.004643145,0.1923278,0.0005791479,0.000138997,0.0005580516,0.00001737816,0.000469339,0.0006081452],"genre_scores_gemma":[0.9981639,0.001087606,0.0003472628,0.00001719032,0.0002168371,0.0000261642,0.0000219089,0.00005131302,0.00006775709],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8979198,"threshold_uncertainty_score":0.5929388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01932685421774284,"score_gpt":0.2699547924331583,"score_spread":0.2506279382154155,"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."}}