{"id":"W3127637594","doi":"10.1109/tia.2021.3057037","title":"Investigation of Critical Parameters for Selecting Energy-Optimal Cruising Speed Using a Low-Computation Framework","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Industry Applications","topic":"Vehicle emissions and performance","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Computation; SPARK (programming language); MATLAB; Energy (signal processing); Computer science; Control theory (sociology); Speedup; Inverter; Critical speed; Control engineering; Automotive engineering; Simulation; Algorithm; Engineering; Voltage; Artificial intelligence; Mathematics; Mechanical engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000857725,0.0007195412,0.0006247578,0.000689958,0.0004742377,0.001091596,0.0009721793,0.0005212558,0.002329909],"category_scores_gemma":[0.003828916,0.0003152935,0.0003942836,0.0003536339,0.0006320625,0.0009498024,0.0006371824,0.0009051003,0.0003524211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007141338,"about_ca_system_score_gemma":0.001224984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007016917,"about_ca_topic_score_gemma":0.005412254,"domain_scores_codex":[0.99967,0.0000810288,0.0000123577,0.00004644235,0.0001319649,0.00005816659],"domain_scores_gemma":[0.9990011,0.0006524118,0.00008125399,0.00007948824,0.0001583338,0.00002736422],"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":[0.00006900523,0.00003387955,0.0007632368,0.0001151965,0.00001111712,0.0000571829,0.00005906249,0.9589607,0.005075705,0.01190572,0.0003571393,0.02259217],"study_design_scores_gemma":[0.000003408152,0.00001460128,0.0001476693,0.000008459068,0.00000300941,0.000009655705,0.00001005262,0.9971315,0.001306541,0.001011067,0.0003500043,0.000004035101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03640525,0.0002607926,0.9549636,0.00008937065,0.00002026826,0.00006356928,0.00004229667,0.0004440943,0.007710766],"genre_scores_gemma":[0.8587086,0.000204551,0.1395005,0.00002842271,0.00001288921,0.00008315857,0.00009310335,0.0001950874,0.001173762],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007016917,"threshold_uncertainty_score":0.0139522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04187271465031653,"score_gpt":0.294915771451733,"score_spread":0.2530430568014165,"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."}}