{"id":"W2539840639","doi":"10.1155/2016/5790464","title":"The Impact of Variable Wind Shear Coefficients on Risk Reduction of Wind Energy Projects","year":2016,"lang":"en","type":"article","venue":"International Scholarly Research Notices","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wind shear; Wind power; Wind speed; Environmental science; Wind gradient; Coefficient of variation; Ranging; Wind profile power law; Mean squared error; Meteorology; Standard deviation; Statistics; Mathematics; Geology; Geodesy; Physics; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00471851,0.0005444667,0.0004420225,0.0008453719,0.0001953496,0.0006256638,0.0004086291,0.0003499335,0.0002844116],"category_scores_gemma":[0.01713463,0.0002027949,0.000305716,0.0006452832,0.0003087163,0.0007328378,0.0005933215,0.0004563696,0.00005388704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003096761,"about_ca_system_score_gemma":0.000409928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002353499,"about_ca_topic_score_gemma":0.002528639,"domain_scores_codex":[0.9980808,0.001080287,0.00009628033,0.0001327436,0.0005050512,0.0001047535],"domain_scores_gemma":[0.9853356,0.01098759,0.001512056,0.0009176417,0.001101425,0.0001457459],"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":[0.0006425146,0.0001104116,0.03239789,0.00007925137,0.00009551075,0.00008883498,0.00009883293,0.8249506,0.007471398,0.001277473,0.0001924972,0.1325949],"study_design_scores_gemma":[0.00003165292,0.0008160832,0.02286421,0.00001941948,0.00005111873,0.00006572858,0.00008943649,0.9643021,0.01056839,0.0008870605,0.0002748993,0.0000298178],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8890525,0.0002354596,0.1094768,0.00007843607,0.0000121796,0.00003990325,0.00007064214,0.0001274234,0.0009065034],"genre_scores_gemma":[0.9796889,0.00005967156,0.02013531,0.000004508696,0.000003073875,0.000007985816,0.00003127292,0.000008291195,0.0000609786],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00471851,"threshold_uncertainty_score":0.0249542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04039075195571953,"score_gpt":0.3285260871310832,"score_spread":0.2881353351753636,"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."}}