{"id":"W2105644046","doi":"10.1109/pes.2009.5275966","title":"Novel method for estimating the CF of variable speed wind turbines","year":2009,"lang":"en","type":"article","venue":"","topic":"Wind Energy Research and Development","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Extrapolation; Wind speed; Variable (mathematics); Wind power; Tower; Turbine; Control theory (sociology); Variable speed wind turbine; Power (physics); Computer science; Mathematics; Engineering; Meteorology; Statistics; Mathematical analysis; Aerospace engineering; Artificial intelligence; Structural 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000490035,0.0008451515,0.0005874615,0.001312429,0.0002576149,0.0004991933,0.001005403,0.0007607079,0.001391339],"category_scores_gemma":[0.002777997,0.0003478813,0.000410141,0.0007483171,0.0003304286,0.001607302,0.0005152706,0.0008737047,0.00053461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004145553,"about_ca_system_score_gemma":0.0006673177,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00260075,"about_ca_topic_score_gemma":0.00236411,"domain_scores_codex":[0.9994236,0.00008661951,0.00002448137,0.0001482181,0.0002936727,0.00002342476],"domain_scores_gemma":[0.998952,0.0003802611,0.0001581763,0.0001123609,0.0003737682,0.00002338824],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001560796,0.00008861872,0.003963085,0.0002898262,0.0000801232,0.000205778,0.0001337466,0.2844191,0.06596689,0.01771522,0.003217533,0.623764],"study_design_scores_gemma":[0.00001593185,0.0000483592,0.001209751,0.00002029953,0.00001631866,0.0002424091,0.00001631287,0.9804204,0.01026061,0.002934781,0.004776669,0.00003820901],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002919279,0.00008207893,0.9963827,0.00001307808,0.00002111971,0.00001197921,0.00003444605,0.0001710097,0.0003642361],"genre_scores_gemma":[0.2406304,0.0004008392,0.7559164,0.00004213535,0.0001054154,0.0001166264,0.0003234724,0.0001228481,0.002341868],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00260075,"threshold_uncertainty_score":0.00517118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02295974737455473,"score_gpt":0.2830422430535542,"score_spread":0.2600824956789994,"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."}}