{"id":"W2751207407","doi":"10.1109/tmag.2017.2748099","title":"Incorporating Control Strategies Into the Optimization of Synchronous AC Machines: A Comparison of Methodologies","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Magnetics","topic":"Electric Motor Design and Analysis","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Magnetic reluctance; Torque; Torque ripple; Direct torque control; Synchronous motor; Control theory (sociology); Finite element method; Control engineering; Ripple; Metric (unit); Machine control; Magnet; Control (management); Mechanical engineering; Engineering; Physics; Electrical engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001576167,0.001329254,0.0009970912,0.0009366602,0.0002337515,0.0011571,0.0008279355,0.00071818,0.001295181],"category_scores_gemma":[0.002689579,0.0004814014,0.0006888782,0.0008332632,0.0004202564,0.0008935009,0.00054619,0.0006559945,0.0003134018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003923158,"about_ca_system_score_gemma":0.0006116285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006349155,"about_ca_topic_score_gemma":0.0006956205,"domain_scores_codex":[0.9990311,0.0003668763,0.00007897334,0.00009435102,0.000389675,0.00003913507],"domain_scores_gemma":[0.998942,0.0005596869,0.0001467301,0.0001067587,0.0002198614,0.00002511189],"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":[0.00010291,0.0001946486,0.000532322,0.000663974,0.0001160658,0.00004957248,0.0001369623,0.63451,0.006291958,0.02257992,0.0004737671,0.3343479],"study_design_scores_gemma":[0.00004659521,0.0003551817,0.0003119497,0.0001232779,0.00005160606,0.00005382223,0.00004928325,0.9813473,0.004591941,0.007352896,0.005692426,0.00002365865],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00968461,0.001724373,0.982947,0.00005808835,0.00002975834,0.00006527736,0.00001325764,0.000150789,0.005326854],"genre_scores_gemma":[0.4551781,0.004800686,0.5369028,0.00009438206,0.000100418,0.0002903389,0.00006213953,0.0002522646,0.002318872],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001576167,"threshold_uncertainty_score":0.00833571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02878096791497802,"score_gpt":0.2941244003925862,"score_spread":0.2653434324776082,"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."}}