{"id":"W2523094825","doi":"10.3390/en9100762","title":"Energy-Efficient Speed Profile Approximation: An Optimal Switching Region-Based Approach with Adaptive Resolution","year":2016,"lang":"en","type":"article","venue":"Energies","topic":"Railway Systems and Energy Efficiency","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Natural Science Foundation of China","keywords":"Regenerative brake; Mode (computer interface); Control theory (sociology); Brake; Point (geometry); Computer science; Energy (signal processing); Optimal control; Energy consumption; Automotive engineering; Mathematical optimization; Engineering; Control (management); Mathematics; Electrical engineering","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":[0.0001648229,0.0002681052,0.0002251282,0.0001668823,0.0001644223,0.00005932417,0.0002008226,0.0001055056,0.00001399983],"category_scores_gemma":[0.000008452344,0.0001720219,0.00005675212,0.0002879621,0.00006783778,0.0002502899,0.00001993949,0.00007690053,0.000007379026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001390804,"about_ca_system_score_gemma":0.00005147626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008706923,"about_ca_topic_score_gemma":0.00001100546,"domain_scores_codex":[0.9985961,0.00005169481,0.0002634552,0.0003676616,0.0003263605,0.0003946808],"domain_scores_gemma":[0.9992855,0.00004390634,0.00007292512,0.000410557,0.0000772152,0.0001099235],"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":[0.00006600509,0.00006049747,0.00001700322,0.00002323856,0.00002017168,0.000005958761,0.0002689889,0.980159,0.004117475,0.007148132,0.0002010684,0.007912503],"study_design_scores_gemma":[0.0005737836,0.0001564828,0.00009180712,0.0001096912,0.00001176393,0.0000230447,0.0004449705,0.9766858,0.02032847,0.00001489423,0.001207093,0.0003521745],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3216152,0.0001793438,0.6661736,0.00003168019,0.0001644717,0.000104488,0.00000408008,0.0005911906,0.01113598],"genre_scores_gemma":[0.9844459,0.000005851408,0.01466099,0.0000119273,0.0002339019,0.00008259717,0.0000182121,0.00005999146,0.0004805914],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6628308,"threshold_uncertainty_score":0.701485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01335329172057272,"score_gpt":0.1853548307640979,"score_spread":0.1720015390435252,"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."}}