{"id":"W1549882955","doi":"","title":"Efficient simulation method for comparison of brush and brushless DC motors for light traction application","year":2009,"lang":"en","type":"article","venue":"European Conference on Power Electronics and Applications","topic":"Electric Motor Design and Analysis","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Brushed DC electric motor; Brush; DC motor; Armature (electrical engineering); Commutator; Traction motor; Traction (geology); Magnet; Computer science; Automotive engineering; Synchronous motor; Electric motor; AC motor; Electrical engineering; Engineering; Mechanical engineering; Physics","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":[0.000377425,0.0005228354,0.0004717374,0.0005258555,0.0003806501,0.000465269,0.0008364298,0.0006437816,0.007193394],"category_scores_gemma":[0.0009802273,0.0002551866,0.0003930778,0.0004410321,0.0001221352,0.000478254,0.0002726816,0.0005285114,0.001121028],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003102485,"about_ca_system_score_gemma":0.0007050262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002464976,"about_ca_topic_score_gemma":0.002081799,"domain_scores_codex":[0.9998053,0.00003595912,0.00001232373,0.00001707378,0.0001154322,0.00001390017],"domain_scores_gemma":[0.9996945,0.0001110089,0.00001887265,0.00003545094,0.0001281067,0.0000122088],"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":[0.0002293391,0.0001713971,0.001361985,0.0004285953,0.00007989777,0.0001888568,0.0001909817,0.7866532,0.05286466,0.02429145,0.006409885,0.1271297],"study_design_scores_gemma":[0.0000184295,0.00003029611,0.0001382336,0.000009887613,0.0000094897,0.00002730998,0.000009655666,0.9886404,0.005185897,0.001117118,0.00480704,0.000006167915],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01329975,0.0001452193,0.9774394,0.00005247791,0.00008173168,0.000120329,0.0002747357,0.001940648,0.006645766],"genre_scores_gemma":[0.4954238,0.0005303437,0.4907389,0.00005482042,0.00003978666,0.001043863,0.001399298,0.0008194282,0.009949701],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007193394,"threshold_uncertainty_score":0.0240643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01716609657145815,"score_gpt":0.2990302173027999,"score_spread":0.2818641207313418,"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."}}