{"id":"W2344023576","doi":"10.1109/irsec.2015.7455141","title":"Modeling and simulation of a wind model using a spectral representation method","year":2015,"lang":"en","type":"article","venue":"","topic":"Wind Energy Research and Development","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Abitibi-Témiscamingue","funders":"","keywords":"Wind speed; Spectral density; Autocorrelation; Wind power; Turbulence; Turbine; MATLAB; Log wind profile; Computer science; Probability density function; Wind profile power law; Mathematics; Physics; Wind gradient; Meteorology; Engineering; Aerospace engineering","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":[0.000403673,0.0004356524,0.0004209128,0.0004308611,0.0002751957,0.0005195747,0.0005047885,0.0007402301,0.001291339],"category_scores_gemma":[0.0007761768,0.0002212982,0.0006687568,0.0003483053,0.0003214709,0.0008989259,0.0003567968,0.000530392,0.0002875808],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002594519,"about_ca_system_score_gemma":0.0004669823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003640977,"about_ca_topic_score_gemma":0.001933048,"domain_scores_codex":[0.9998022,0.00006955581,0.00001545447,0.00003029242,0.00006054138,0.00002194481],"domain_scores_gemma":[0.9997616,0.0001197071,0.00003185638,0.00002994905,0.0000469515,0.000009983909],"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":[0.00001504449,0.00002268637,0.0003337681,0.00002537917,0.00001225279,0.0000477973,0.00003540299,0.9790364,0.003885349,0.008196513,0.0001509794,0.008238418],"study_design_scores_gemma":[0.000001153827,0.000004511543,0.00002156304,9.898804e-7,8.166743e-7,0.000004666583,0.000001553112,0.999285,0.0002014324,0.0003581014,0.0001189251,0.000001307031],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02448974,0.00007041836,0.972994,0.00005496838,0.0000269403,0.00002970858,0.00004536334,0.000403362,0.001885548],"genre_scores_gemma":[0.7582151,0.0002811817,0.2377129,0.00004036804,0.00003863881,0.000213702,0.0001971486,0.00010499,0.003195948],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003640977,"threshold_uncertainty_score":0.00723958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1179476965623327,"score_gpt":0.3613384206522534,"score_spread":0.2433907240899207,"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."}}