{"id":"W4409196544","doi":"10.1016/j.energy.2025.135793","title":"Multiobjective eco-driving speed optimisation with real-time traffic: Balancing fuel, NOx, and travel time","year":2025,"lang":"en","type":"article","venue":"Energy","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Xi’an Jiaotong-Liverpool University; National Key Research and Development Program of China; China Scholarship Council; Horizon 2020 Framework Programme; National Natural Science Foundation of China","keywords":"NOx; Automotive engineering; Travel time; Fuel efficiency; Environmental science; Nitrogen oxides; Transport engineering; Computer science; Engineering; Waste management; Combustion; Chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006125657,0.0007409836,0.000489012,0.0004351195,0.0001712922,0.0006083553,0.0006670538,0.0005540322,0.0006619687],"category_scores_gemma":[0.001001911,0.0002820765,0.0003914541,0.0002816369,0.0003449655,0.0005988522,0.0006257751,0.0005944176,0.0001350396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005502916,"about_ca_system_score_gemma":0.0008673266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003876223,"about_ca_topic_score_gemma":0.003863934,"domain_scores_codex":[0.999781,0.0000590049,0.000007501503,0.00004307301,0.00006705249,0.00004235503],"domain_scores_gemma":[0.999687,0.0001189291,0.00006918694,0.00002409424,0.00007081907,0.00002999114],"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":[0.00001998228,0.00002793124,0.0005670633,0.00002149933,0.00001318893,0.00001478068,0.00001163719,0.9830488,0.002159749,0.0007313954,0.00008974067,0.01329412],"study_design_scores_gemma":[0.000003642365,0.00002313036,0.0001991845,0.000002328479,0.000002855378,0.000005148608,0.000004819381,0.9985986,0.0006096645,0.0003674199,0.0001806837,0.000002445205],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1603815,0.00026327,0.8325297,0.0001480499,0.00003241977,0.00006399915,0.00006097042,0.0003743695,0.006145659],"genre_scores_gemma":[0.9545254,0.00006442105,0.04385797,0.0000326216,0.000008232285,0.00004895042,0.00006037864,0.00003873357,0.001363394],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003876223,"threshold_uncertainty_score":0.007707298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003241530428690282,"score_gpt":0.1888234800877834,"score_spread":0.1855819496590931,"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."}}