{"id":"W4403544853","doi":"10.1155/2024/8574868","title":"Enhancing the Efficiency of Horizontal Axis Wind Turbines Through Optimization of Blade Parameters","year":2024,"lang":"en","type":"article","venue":"Journal of Engineering","topic":"Wind Energy Research and Development","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Horizontal axis; Blade (archaeology); Vertical axis; Wind power; Marine engineering; Mechanical engineering; Environmental science; Aerospace engineering; Geology; Engineering; Structural engineering; Engineering drawing; Electrical 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":[0.0003018545,0.0005344373,0.0002654162,0.0002930885,0.0001573893,0.0004726097,0.0002046917,0.000226941,0.0009684916],"category_scores_gemma":[0.0006782079,0.0001460523,0.0001907213,0.0002095807,0.0001414271,0.0003607603,0.0001832793,0.0002032063,0.0003794005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001477114,"about_ca_system_score_gemma":0.0002858966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007411049,"about_ca_topic_score_gemma":0.001539295,"domain_scores_codex":[0.9998909,0.00002193458,0.000007062446,0.0000165025,0.00004640213,0.0000172353],"domain_scores_gemma":[0.999813,0.00006501316,0.00005213016,0.00002164888,0.00004208793,0.000006158185],"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":[0.0002540484,0.0002457275,0.01722502,0.0004400714,0.00006647032,0.0001671566,0.00009748613,0.5577759,0.2560835,0.002343642,0.001169551,0.1641315],"study_design_scores_gemma":[0.00006095491,0.0009735345,0.01806958,0.00005634263,0.00005289334,0.0001636779,0.0001494144,0.8420777,0.1301604,0.001058062,0.007135308,0.00004215042],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8102309,0.0007379849,0.1779421,0.0001042627,0.00003283784,0.00007471417,0.0002062932,0.0005206671,0.01015022],"genre_scores_gemma":[0.9588622,0.0002184683,0.03972931,0.0000206305,0.000003441994,0.00002786219,0.0001099333,0.00009597147,0.0009321565],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009684916,"threshold_uncertainty_score":0.00323993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008002304006390612,"score_gpt":0.2130562123873453,"score_spread":0.2050539083809547,"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."}}