{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002386667,0.00004760449,0.000203435,0.0000339252,0.00009592294,0.0001151622,0.0001651516,0.00006436487,0.0001659408],"category_scores_gemma":[0.00002831244,0.0001227554,0.00003657406,0.0001114942,0.0001190331,0.0001568442,0.00005812241,0.00006757368,0.00003231109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001213922,"about_ca_system_score_gemma":0.00003806782,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05065367,"about_ca_topic_score_gemma":0.006094645,"domain_scores_codex":[0.9990749,0.0001145922,0.0001344654,0.0003409183,0.0001659588,0.0001691016],"domain_scores_gemma":[0.9994741,0.00005850868,0.0001165986,0.0002193289,0.00006587961,0.00006554839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002896132,0.0006339418,0.007278882,0.001270608,0.0000229326,0.00006856704,0.001053743,0.01391153,0.06767634,0.0001177886,0.001620764,0.9060553],"study_design_scores_gemma":[0.001069608,0.0005255635,0.845331,0.0004448135,0.00002883135,0.00002676473,0.002210513,0.1498271,0.00007545155,0.0001232798,0.0001109482,0.0002262424],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9883953,0.00006731784,0.01016434,0.0001098368,0.0001119029,0.0006456422,0.0002909822,0.00003184087,0.0001828631],"genre_scores_gemma":[0.9969177,0.00001496161,0.002838908,0.00001812239,0.000004890108,0.000006177772,0.00005648485,0.000006392328,0.0001363799],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9058291,"threshold_uncertainty_score":0.9556681,"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."}}