{"id":"W2915960189","doi":"10.1109/tte.2019.2899740","title":"Back EMF, Torque–Angle, and Core Loss Characterization of a Variable-Flux Permanent-Magnet Machine","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Transportation Electrification","topic":"Electric Motor Design and Analysis","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Alnico; Magnet; Torque; Flux linkage; Counter-electromotive force; Control theory (sociology); Rotor (electric); Core (optical fiber); Magnetic flux; Electromotive force; Direct torque control; Mechanics; Computer science; Engineering; Mechanical engineering; Electromagnetic coil; Physics; Voltage; Electrical engineering; Magnetic field; Optics; Induction motor","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004629896,0.0004839512,0.0004368194,0.001108107,0.0002649851,0.000412963,0.0003747131,0.0004085777,0.0010458],"category_scores_gemma":[0.0008855509,0.0001723814,0.0002644195,0.0004332565,0.0003775787,0.0005600025,0.0001254415,0.0001945234,0.0003087846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002749641,"about_ca_system_score_gemma":0.0001517513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000385577,"about_ca_topic_score_gemma":0.000361277,"domain_scores_codex":[0.9996552,0.0000490127,0.00001873902,0.00004067301,0.0002124319,0.00002390673],"domain_scores_gemma":[0.9993305,0.0002729258,0.0000999458,0.00007730213,0.0002003429,0.0000189331],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008937055,0.0003333916,0.01123463,0.0004746188,0.0000614852,0.0003299914,0.0003553632,0.08243887,0.7088245,0.001880913,0.00129321,0.1918793],"study_design_scores_gemma":[0.00005653543,0.001415416,0.06073708,0.00003840541,0.00004987294,0.0007169839,0.0001291197,0.4185153,0.511744,0.001281917,0.005241304,0.00007400833],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.758579,0.0003814998,0.2338123,0.0001070631,0.00002601683,0.00007021162,0.0003189124,0.0006616521,0.00604328],"genre_scores_gemma":[0.9864325,0.00008103073,0.01224671,0.000008658608,0.000005651015,0.00002316732,0.0001372593,0.00003685505,0.001028206],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001108107,"threshold_uncertainty_score":0.003498554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007059429652655757,"score_gpt":0.191802141659265,"score_spread":0.1847427120066093,"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."}}