{"id":"W2103077269","doi":"10.1002/we.199","title":"State modelling of self‐excited induction generator for wind power applications","year":2006,"lang":"en","type":"article","venue":"Wind Energy","topic":"Wind Turbine Control Systems","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Université du Québec; Université du Québec en Abitibi-Témiscamingue","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada; National Science Council","keywords":"Induction generator; Wind power; Control theory (sociology); Transient (computer programming); Engineering; Shunt (medical); Voltage; Doubly fed electric machine; Overvoltage; Electric power system; AC power; Power (physics); Computer science; Electrical engineering; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001228094,0.0003826824,0.0003155542,0.0001914107,0.0001809908,0.0005075686,0.0003636526,0.0004379904,0.001840672],"category_scores_gemma":[0.0002658328,0.0001624944,0.0002625603,0.0001484498,0.0002209271,0.0004475588,0.0001983035,0.0002480609,0.0003625652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002631816,"about_ca_system_score_gemma":0.0001980134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001999437,"about_ca_topic_score_gemma":0.001610324,"domain_scores_codex":[0.9999336,0.00002113396,0.000004235666,0.000009480365,0.00002443441,0.000007099023],"domain_scores_gemma":[0.9999065,0.00003593156,0.00001845079,0.00001324121,0.00002107718,0.000004731025],"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":[0.0000451329,0.00001786355,0.0005764604,0.00003432253,0.00001022165,0.00008535643,0.0000444403,0.9811639,0.008157403,0.003022742,0.0002456698,0.006596485],"study_design_scores_gemma":[0.000002853069,0.00002151114,0.0001339128,0.000001699682,0.000002540729,0.000006584258,0.000003616853,0.9983488,0.0006787922,0.0004958136,0.0003023176,0.000001454883],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2823143,0.0002285449,0.6985918,0.0001314856,0.00004460905,0.00009616671,0.0002881838,0.001404866,0.0169002],"genre_scores_gemma":[0.9925573,0.00007584912,0.004791568,0.000006435122,0.000003411172,0.0000433861,0.0001041617,0.00001382132,0.002404055],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001999437,"threshold_uncertainty_score":0.006157696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00844348973967283,"score_gpt":0.1765381707574177,"score_spread":0.1680946810177448,"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."}}