{"id":"W2801277833","doi":"10.4271/08-07-01-0002","title":"Design, Analysis, and Optimization of a Multi-Speed Powertrain for Class-7 Electric Trucks","year":2018,"lang":"en","type":"article","venue":"SAE International journal of alternative powertrains","topic":"Electric and Hybrid Vehicle Technologies","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Powertrain; Truck; Automotive engineering; Class (philosophy); Computer science; Engineering; Torque; Artificial intelligence","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":[0.0004087828,0.00017547,0.0003576887,0.00115005,0.00003632662,0.00005160024,0.0004335287,0.0000808056,0.0000330585],"category_scores_gemma":[0.0002667555,0.0001594952,0.0001772485,0.0005078046,0.0001287074,0.0002900338,0.00002709773,0.0001863844,8.309964e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001285978,"about_ca_system_score_gemma":0.00005535277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001045656,"about_ca_topic_score_gemma":0.00001978646,"domain_scores_codex":[0.9986826,0.00003661159,0.0005832055,0.0001487038,0.0003378416,0.0002110148],"domain_scores_gemma":[0.9981595,0.0002212199,0.0003682732,0.00009929067,0.001089485,0.00006223493],"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":[0.001409075,0.0006299841,0.004977125,0.0000651744,0.01986746,0.0001009224,0.003691945,0.5828738,0.2542397,0.004762776,0.001276635,0.1261054],"study_design_scores_gemma":[0.002237232,0.0009338374,0.005382202,0.00006693345,0.0002928167,0.00009079016,0.0001224286,0.881799,0.1072018,0.001399581,0.0002402623,0.000233112],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1495711,0.0005443849,0.8489143,0.0002046099,0.0003799784,0.0001582467,0.00002423636,0.00005230549,0.0001508337],"genre_scores_gemma":[0.9410724,0.0006902281,0.05794397,0.00004992046,0.0001865042,0.000002984551,0.000006452649,0.00002405306,0.00002345311],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7915013,"threshold_uncertainty_score":0.6504025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02191516836806946,"score_gpt":0.2862115296059154,"score_spread":0.2642963612378459,"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."}}