{"id":"W4399734102","doi":"10.1109/tie.2024.3398669","title":"Intelligent Efficient Control for Brushless Doubly-Fed Induction Machines","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Industrial Electronics","topic":"Multilevel Inverters and Converters","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; École de Technologie Supérieure; University of Saskatchewan","funders":"","keywords":"Machine control; Induction motor; Control engineering; Computer science; Control theory (sociology); DC motor; Direct torque control; Control (management); Engineering; Electrical engineering; Artificial intelligence; Voltage","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":[0.000161947,0.0003158784,0.0002193237,0.0001455103,0.0001715948,0.0003621294,0.0003072667,0.0001656771,0.0006054998],"category_scores_gemma":[0.0002836512,0.00008022444,0.0001629756,0.0001025133,0.000176509,0.0002275631,0.0001926326,0.0002773855,0.0001320382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001677207,"about_ca_system_score_gemma":0.0001215432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004420611,"about_ca_topic_score_gemma":0.0008661803,"domain_scores_codex":[0.9998813,0.00001619264,0.000009121833,0.0000203639,0.00006057135,0.00001239898],"domain_scores_gemma":[0.9999195,0.00002182002,0.00001900533,0.00001064568,0.00002423861,0.000004815063],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003126775,0.0001863877,0.001476533,0.0004050305,0.00007945111,0.0002314351,0.0002820499,0.1666642,0.2408326,0.02548444,0.002107646,0.5619376],"study_design_scores_gemma":[0.000042766,0.000330887,0.002272236,0.00001931517,0.00002927464,0.0001333178,0.00001753316,0.9600966,0.02656357,0.003595942,0.00688238,0.00001614077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05077798,0.0005128352,0.9429247,0.00007793923,0.00006308275,0.00004140897,0.000016817,0.0005269271,0.005058279],"genre_scores_gemma":[0.963685,0.0001773845,0.0346621,0.00002839612,0.00002082906,0.00003614618,0.00002007192,0.00001247399,0.001357623],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0006054998,"threshold_uncertainty_score":0.002025604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03011791884823484,"score_gpt":0.2489227818443759,"score_spread":0.218804862996141,"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."}}