{"id":"W2120103362","doi":"10.1109/ccece.2007.360","title":"A New Wind Power Plant Simulation Method to Study Power Quality","year":2007,"lang":"en","type":"article","venue":"","topic":"Wind Energy Research and Development","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Ministry of Science Research and Technology","keywords":"Wind power; Turbine; Power optimizer; Marine engineering; Power station; Aerodynamics; Wind profile power law; Wind speed; Environmental science; Automotive engineering; Engineering; Maximum power point tracking; Meteorology; Electrical engineering; Voltage; Aerospace engineering; Physics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001077909,0.0001104804,0.0001283728,0.000117984,0.00003479452,0.00003108559,0.00009509694,0.00004361481,0.000987379],"category_scores_gemma":[0.00004284873,0.00009286321,0.00002663618,0.0002242557,0.000002060905,0.00006952321,0.00004233973,0.00009051951,0.0001612778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007136747,"about_ca_system_score_gemma":0.00002571256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001553929,"about_ca_topic_score_gemma":0.0001216754,"domain_scores_codex":[0.9989094,0.00003472299,0.0002366674,0.0001570799,0.0003311849,0.0003309902],"domain_scores_gemma":[0.99932,0.0001535454,0.000008184407,0.0001744446,0.00003177298,0.0003120402],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003326854,0.0003007465,0.01339312,0.00001474179,0.0003394462,0.0001027667,0.009873652,0.8767406,0.003876978,0.001758689,0.01318899,0.08007752],"study_design_scores_gemma":[0.001811183,0.0004417509,0.8843733,0.00001326676,0.000008772985,0.000004964445,0.002760262,0.008217895,0.01155132,0.0003608303,0.08969907,0.0007573867],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3404138,0.00001184581,0.6248195,0.00003914519,0.00009846765,0.0001885222,0.000001517015,0.0001716111,0.0342556],"genre_scores_gemma":[0.9458119,2.407903e-7,0.05265683,0.0001025119,0.00003699616,0.000001909662,0.000003161943,0.0000154036,0.001371059],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8709802,"threshold_uncertainty_score":0.9999259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03552252758505881,"score_gpt":0.3665985715929039,"score_spread":0.3310760440078451,"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."}}