{"id":"W4410887350","doi":"10.1109/syscon64521.2025.11014787","title":"Data-Driven Modeling and Simulation Approach for Energy Demand Prediction of Off-Road Electric Truck","year":2025,"lang":"en","type":"article","venue":"","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Truck; Computer science; Energy (signal processing); Data modeling; Automotive engineering; Data mining; Database; Engineering; Statistics; Mathematics","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":[0.00006995984,0.00005453065,0.00008357203,0.00007681426,0.00003870604,0.000008268027,0.00006152922,0.00004910844,0.000002743024],"category_scores_gemma":[0.000007943614,0.00004873697,0.00001108586,0.0001241717,0.000003462784,0.000137056,0.00002067965,0.00003169063,5.154264e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001015912,"about_ca_system_score_gemma":0.000009740657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009653679,"about_ca_topic_score_gemma":0.000002003565,"domain_scores_codex":[0.9996308,0.000004029056,0.0001422761,0.000104224,0.00004031851,0.00007832968],"domain_scores_gemma":[0.999782,0.00002124918,0.00001110014,0.0001431328,0.00002471846,0.00001782785],"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":[0.000007833567,0.000007024074,0.0002497293,0.00008047888,0.0000160933,8.846113e-9,0.00001195588,0.9139051,0.0009031603,0.0001582469,0.0001295643,0.08453084],"study_design_scores_gemma":[0.000233972,0.0000129863,0.0002798463,0.00001319741,0.0000175009,2.78796e-7,0.000009377261,0.9980432,0.0005204315,0.0000491484,0.0007794455,0.00004055571],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2169531,0.000494559,0.7806462,0.000003859699,0.00003034514,0.00007320193,0.00002208427,0.0000578056,0.001718902],"genre_scores_gemma":[0.9948145,0.0002730417,0.004628648,0.000006269882,0.00002826994,0.000008604738,0.0001003431,0.000006458929,0.0001338665],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7778614,"threshold_uncertainty_score":0.1987436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02420224969608531,"score_gpt":0.2476337124638557,"score_spread":0.2234314627677704,"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."}}