{"id":"W2759431767","doi":"10.1109/tte.2017.2755549","title":"Acoustic Noise-Based Uniform Permanent-Magnet Demagnetization Detection in SPMSM for High-Performance PMSM Drive","year":2017,"lang":"en","type":"article","venue":"IEEE Transactions on Transportation Electrification","topic":"Electric Motor Design and Analysis","field":"Engineering","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Demagnetizing field; Acoustics; Noise (video); Magnet; SIGNAL (programming language); Computer science; Engineering; Physics; Electrical engineering; Magnetic field; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002104347,0.0002613842,0.0002375607,0.000548192,0.0005048978,0.00008162201,0.0002125997,0.00021992,0.00003821154],"category_scores_gemma":[0.00000819383,0.0003043436,0.0001053649,0.0004545762,0.00004258041,0.0004966047,1.504922e-8,0.0002857844,0.00001915465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000250425,"about_ca_system_score_gemma":0.0000544753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008588175,"about_ca_topic_score_gemma":0.001095045,"domain_scores_codex":[0.9985167,0.00002649147,0.0005049721,0.000352976,0.0002547854,0.0003440653],"domain_scores_gemma":[0.9991168,0.00007794885,0.000166125,0.000412926,0.0001508854,0.00007525081],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001040188,0.00009376162,0.00008600616,0.0001040714,0.00002680626,6.921858e-7,0.0001011416,0.4594513,0.437997,0.0000349105,0.000007181181,0.1019931],"study_design_scores_gemma":[0.0009674691,0.0001858922,0.02146551,0.00002943437,0.0001177333,4.759303e-7,0.000007476441,0.406121,0.570796,0.00006257287,0.00001763296,0.0002288569],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3306844,0.00002247547,0.6681932,0.00005725072,0.000194105,0.0005682862,0.0000380716,0.0001916605,0.00005059631],"genre_scores_gemma":[0.9975958,0.0002353007,0.001100394,0.00003124238,0.00005068542,0.0005712631,0.0002072423,0.00005897026,0.00014904],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6670928,"threshold_uncertainty_score":0.9999409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008397689955547061,"score_gpt":0.2085841935774419,"score_spread":0.2001865036218948,"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."}}