{"id":"W2031540086","doi":"10.1049/iet-epa.2011.0281","title":"Analytical modelling and parametric sensitivity analysis for the PMSM steady‐state performance prediction","year":2013,"lang":"en","type":"article","venue":"IET Electric Power Applications","topic":"Hydraulic and Pneumatic Systems","field":"Engineering","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Sensitivity (control systems); Steady state (chemistry); Parametric statistics; Control theory (sociology); Computer science; Engineering; Mathematics; Electronic engineering; Artificial intelligence; Statistics; Control (management); Chemistry","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":[0.0003031153,0.000121833,0.0001881045,0.0002201342,0.0001755751,0.00007389369,0.00007941832,0.00005808624,0.00001244073],"category_scores_gemma":[0.0000128543,0.00009442522,0.0000752796,0.001664822,0.00002259996,0.000118282,0.000008712303,0.0001214873,0.00003583344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004849046,"about_ca_system_score_gemma":0.00001268682,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006225191,"about_ca_topic_score_gemma":0.000003315858,"domain_scores_codex":[0.9991572,0.00002132123,0.0002527438,0.0001849223,0.0001348683,0.0002488728],"domain_scores_gemma":[0.9990166,0.00049695,0.00003986305,0.0002962637,0.00007381175,0.00007648252],"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":[0.000001470134,0.00001656615,0.00214309,0.00002920277,0.0003617233,5.295487e-8,0.0001497588,0.9882929,0.00009469215,0.0001636886,0.0005263088,0.00822052],"study_design_scores_gemma":[0.0000820502,0.00001658708,0.01008844,0.000002590802,0.0002149408,0.000005213247,0.00002503974,0.9874543,0.00006465609,0.0001682736,0.001778919,0.00009898732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2062459,0.0003389004,0.7917064,0.00006212252,0.00002592587,0.0007884353,0.00001222628,0.0001242131,0.0006957754],"genre_scores_gemma":[0.998129,0.000294619,0.0003815015,0.00002195038,0.00004169057,0.0009589971,0.0000137637,0.00001663075,0.0001418233],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7918831,"threshold_uncertainty_score":0.3850549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01201086150537677,"score_gpt":0.2105216828343557,"score_spread":0.1985108213289789,"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."}}