{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007196536,0.000145745,0.0001958101,0.0001240219,0.00004767037,0.0000197555,0.00009714344,0.00009761227,0.000007526012],"category_scores_gemma":[0.000001611096,0.0001528654,0.00007041974,0.0002038375,0.00001166947,0.0001053304,0.000008429516,0.00005528894,0.000004246067],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006102809,"about_ca_system_score_gemma":0.00001813001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002456696,"about_ca_topic_score_gemma":0.00001864467,"domain_scores_codex":[0.9991467,0.00001254013,0.0003307874,0.0001702279,0.000117667,0.000222053],"domain_scores_gemma":[0.9995416,0.00002478772,0.00006218808,0.000229798,0.0000958905,0.00004570659],"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":[0.000004858228,0.0000266958,0.00002479604,0.00002986933,0.00004769675,2.717914e-7,0.00006543651,0.9782158,0.01829272,0.002128096,0.0007982389,0.000365528],"study_design_scores_gemma":[0.0007188685,0.00002982253,0.0001671042,0.00001506911,0.00002998759,0.000004182177,0.00001830123,0.8560293,0.01612888,0.001279255,0.125313,0.0002662438],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3175476,0.0006033102,0.6790465,0.00002971243,0.0003312721,0.0002780673,0.00005380544,0.0003018007,0.001807934],"genre_scores_gemma":[0.9969016,0.000007833323,0.001992934,0.00001447354,0.0005565177,0.00008308707,0.00006130352,0.00005516092,0.000327097],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.679354,"threshold_uncertainty_score":0.6233671,"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."}}