{"id":"W2126013616","doi":"10.1109/ccece.2008.4564727","title":"The effects of enviromental parameters on wind turbine power PDF curve","year":2008,"lang":"en","type":"article","venue":"Conference proceedings - Canadian Conference on Electrical and Computer Engineering","topic":"Wind Energy Research and Development","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Weibull distribution; Turbine; Wind power; Wind speed; Density of air; Probability density function; Environmental science; Altitude (triangle); Meteorology; Wind profile power law; Power (physics); Power density; Marine engineering; Atmospheric sciences; Engineering; Mathematics; Statistics; Electrical engineering; Physics; Aerospace engineering; Thermodynamics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007594979,0.0004424196,0.0003045953,0.0005026318,0.0003023398,0.0006499268,0.000286569,0.0006450437,0.001272463],"category_scores_gemma":[0.00640178,0.0002606995,0.0004304666,0.0004469118,0.0005006691,0.0008580278,0.0002836261,0.0005769682,0.0002574926],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003240158,"about_ca_system_score_gemma":0.0001731945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001946451,"about_ca_topic_score_gemma":0.002053903,"domain_scores_codex":[0.9993457,0.000172764,0.00003810844,0.0001246671,0.0002084102,0.0001103031],"domain_scores_gemma":[0.9929938,0.005124066,0.0005131452,0.0005344244,0.0006839043,0.0001506593],"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":[0.001448148,0.0003203377,0.2618415,0.0003333132,0.0003359355,0.003521837,0.0005327711,0.5732877,0.09998828,0.000964315,0.0007794097,0.05664649],"study_design_scores_gemma":[0.00005814881,0.001546351,0.564496,0.00005889516,0.0003449268,0.002467728,0.001081058,0.2537012,0.1703385,0.001492803,0.004126512,0.0002877089],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.98172,0.0003593287,0.01425954,0.00006680384,0.0000318516,0.00001961424,0.0003526855,0.0002382734,0.002951805],"genre_scores_gemma":[0.99909,0.00008834966,0.0004501162,0.00001010399,0.000003587793,0.000003718528,0.0001167179,0.00002994621,0.0002075551],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001946451,"threshold_uncertainty_score":0.004256845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007736632381573849,"score_gpt":0.1682112614775498,"score_spread":0.160474629095976,"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."}}