{"id":"W1949936154","doi":"","title":"신안풍력발전소 풍력터빈의 성능저하 분석","year":2013,"lang":"ko","type":"article","venue":"태양에너지(한국태양에너지학회 논문집)","topic":"Engineering Applied Research","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Wind power; Nacelle; Environmental science; Turbine; Wind speed; Meteorology; Marine engineering; Engineering; Geography; Electrical engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002158673,0.0001198239,0.0001659691,0.0003262544,0.0002423973,0.0003849258,0.0001718461,0.0001544963,0.001236941],"category_scores_gemma":[0.0005820509,0.00005182421,0.0001210454,0.0003626246,0.0001557094,0.0004514561,0.0000867042,0.0001374783,0.0004342365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003099739,"about_ca_system_score_gemma":0.0002483913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005641853,"about_ca_topic_score_gemma":0.008920577,"domain_scores_codex":[0.9998573,0.00001079601,0.000009590973,0.00004060824,0.00006267355,0.00001903462],"domain_scores_gemma":[0.9996442,0.00006186211,0.00008548973,0.00002714606,0.0001652787,0.00001615613],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003211068,0.0001532047,0.4660172,0.0003109696,0.0001798008,0.0005499332,0.001551776,0.0340489,0.1277945,0.00327852,0.002661444,0.3631327],"study_design_scores_gemma":[0.000006113324,0.0005778559,0.8261612,0.00003828202,0.00009887278,0.0008302987,0.001592568,0.07247121,0.07260725,0.002687277,0.02284008,0.00008900175],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9717411,0.0004538145,0.01862069,0.0001641438,0.00002574464,0.00002498018,0.00039089,0.00008595947,0.008492595],"genre_scores_gemma":[0.9940321,0.0001410151,0.002940837,0.00002665382,0.000007794701,0.00000748566,0.0003416708,0.000006255982,0.002496129],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005641853,"threshold_uncertainty_score":0.01121801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00794338260713252,"score_gpt":0.2160438886533481,"score_spread":0.2081005060462156,"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."}}