{"id":"W4384305381","doi":"10.20906/sbse.v2i1.3063","title":"Otimização de TSF analíticas para SRMs via Algoritmo Enxame de Partículas e Plataforma HIL","year":2022,"lang":"pt","type":"article","venue":"Anais do ... Simpósio Brasileiro de Sistemas Elétricos","topic":"Electric Motor Design and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Control theory (sociology); Torque; Particle swarm optimization; Python (programming language); Switched reluctance motor; Computer science; PID controller; Torque ripple; Physics; Direct torque control; Control engineering; Engineering; Algorithm; Artificial intelligence; Induction motor","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":[0.0005676746,0.0005271419,0.0003380236,0.0008133697,0.0002418735,0.0006257002,0.0002157667,0.0002428271,0.002314614],"category_scores_gemma":[0.001934578,0.0001117687,0.0003434586,0.0004133098,0.0001896637,0.0004183127,0.0001801819,0.0003418532,0.0004110293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000234491,"about_ca_system_score_gemma":0.0003890019,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002100073,"about_ca_topic_score_gemma":0.002823696,"domain_scores_codex":[0.9997899,0.00004816719,0.0000167951,0.00003204676,0.00009117786,0.00002192613],"domain_scores_gemma":[0.9993501,0.0003708819,0.00006959157,0.00005792261,0.0001369458,0.00001451224],"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":[0.0005011635,0.0001070127,0.00617305,0.0004216869,0.00005477542,0.0001873599,0.0004298665,0.1723603,0.07822025,0.003701141,0.001182417,0.736661],"study_design_scores_gemma":[0.0000124217,0.0001509191,0.004057744,0.00003002651,0.0000214165,0.0001269037,0.0001684461,0.9634748,0.02800153,0.001418839,0.002522547,0.00001444755],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1522167,0.0003022744,0.8421481,0.00007595804,0.00002777385,0.0000631757,0.0001132696,0.002290479,0.002762281],"genre_scores_gemma":[0.7882378,0.0001919478,0.2097811,0.00001583476,0.00001158385,0.00005535968,0.0001565326,0.0002052539,0.001344658],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002314614,"threshold_uncertainty_score":0.00774318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02068452959249161,"score_gpt":0.2540937353341862,"score_spread":0.2334092057416945,"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."}}