{"id":"W2927066358","doi":"10.14288/1.0376252","title":"Parameters estimation based on recursive extended least-squares method in dc distribution systems and interior permanent magnet synchronous motors","year":2019,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Magnetic Properties and Applications","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Synchronous motor; Control theory (sociology); Permanent magnet synchronous generator; DC motor; Permanent magnet synchronous motor; Distribution (mathematics); Magnet; Recursive least squares filter; Least-squares function approximation; Mathematics; Computer science; Engineering; Algorithm; Mathematical analysis; Electrical engineering; Statistics; Artificial intelligence","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":[0.0004332237,0.0006389283,0.0004934105,0.0003845603,0.0002389827,0.0005747273,0.0004762688,0.000541717,0.001025259],"category_scores_gemma":[0.001048106,0.000319269,0.0005298394,0.0005262669,0.0003274678,0.0004846795,0.0003974696,0.0008224592,0.0004702947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002694381,"about_ca_system_score_gemma":0.0004532239,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002151206,"about_ca_topic_score_gemma":0.001337733,"domain_scores_codex":[0.999619,0.00009539148,0.00002453407,0.0001057656,0.0001385362,0.00001662408],"domain_scores_gemma":[0.9996872,0.0001161486,0.00006404639,0.00003734158,0.00008879214,0.000006575151],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008798447,0.000052656,0.001291155,0.0004612361,0.00006777485,0.0002020841,0.0002720586,0.5296116,0.03892808,0.01985133,0.002244384,0.4069297],"study_design_scores_gemma":[0.000007511043,0.00006866334,0.0006583774,0.00002394622,0.00001402652,0.00007431148,0.00002354733,0.9826598,0.007853207,0.003077091,0.005516891,0.00002255322],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003500899,0.0004406032,0.9946316,0.00004032657,0.0000233038,0.00001841351,0.00001110632,0.0002736206,0.0010601],"genre_scores_gemma":[0.4708755,0.002989312,0.5177669,0.00009255383,0.0001207516,0.0002483324,0.0001632932,0.0001729903,0.007570424],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002151206,"threshold_uncertainty_score":0.004277349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006660879306830636,"score_gpt":0.1933653980172962,"score_spread":0.1867045187104656,"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."}}