{"id":"W4409473863","doi":"10.1109/tte.2025.3560634","title":"A Fast-Digital Current Regulator Based on Matched Pole–Zero Discretization for PMSM","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Transportation Electrification","topic":"Magnetic Field Sensors Techniques","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Regulator; Control theory (sociology); Discretization; Zero (linguistics); Current (fluid); Physics; Mathematics; Computer science; Mathematical analysis; Chemistry; Artificial intelligence; Philosophy; Control (management)","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":[0.000376355,0.0003671339,0.0004135053,0.0002641711,0.0002922564,0.0005066029,0.0006210627,0.0004595341,0.001820907],"category_scores_gemma":[0.0006033044,0.000190116,0.000409605,0.0003326414,0.0003338881,0.0005443866,0.0003188152,0.0005584363,0.0006272036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003106034,"about_ca_system_score_gemma":0.00048142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007580225,"about_ca_topic_score_gemma":0.0006397162,"domain_scores_codex":[0.9995858,0.00007469092,0.00002374908,0.00009631549,0.0001988194,0.00002065921],"domain_scores_gemma":[0.9997982,0.0000589418,0.00003436445,0.00003486715,0.00006456209,0.000009051579],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003002332,0.0001508116,0.001111209,0.000834777,0.00008007055,0.0002744186,0.0005152286,0.1939908,0.2759027,0.03763581,0.004298923,0.4849052],"study_design_scores_gemma":[0.00009192716,0.000482128,0.0005752564,0.00004776752,0.0000320083,0.0003638818,0.0000399709,0.9170591,0.04950023,0.003139436,0.02862793,0.00004041654],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005144357,0.0003535671,0.99059,0.00006156979,0.00006494897,0.00004318191,0.00001812075,0.0007147768,0.003009568],"genre_scores_gemma":[0.5888162,0.0006121858,0.4048834,0.000142053,0.0000852786,0.0002141656,0.0001101295,0.00007828978,0.005058222],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001820907,"threshold_uncertainty_score":0.006091475,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006933993080378864,"score_gpt":0.2349620665671435,"score_spread":0.2280280734867647,"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."}}