{"id":"W1603907621","doi":"10.1002/we.1614","title":"Global sensitivity analysis of wind turbine power output","year":2013,"lang":"en","type":"article","venue":"Wind Energy","topic":"Wind Energy Research and Development","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor; Wind Energy Institute of Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Turbine; Wind power; Sensitivity (control systems); Control theory (sociology); Amplitude; Rotor (electric); Wind speed; Position (finance); Range (aeronautics); Blade pitch; Computer science; Marine engineering; Engineering; Environmental science; Meteorology; Aerospace engineering; Physics; Electronic engineering; Mechanical engineering; Artificial intelligence; Electrical 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001103704,0.000166935,0.0003235278,0.000212317,0.00003097086,0.00003008477,0.0001071025,0.00009619362,0.0005308093],"category_scores_gemma":[0.00002025839,0.0001506473,0.000141724,0.0009770346,0.00004273851,0.0001295839,0.00006114953,0.00006067891,0.00004522177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009324903,"about_ca_system_score_gemma":0.00003156642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00187065,"about_ca_topic_score_gemma":0.0003208518,"domain_scores_codex":[0.9988484,0.00003457227,0.0002300312,0.0001879244,0.0003082438,0.0003908375],"domain_scores_gemma":[0.9993668,0.00003429329,0.00002407856,0.0002854345,0.00009095109,0.0001984131],"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":[0.00001068888,0.00006038708,0.008406191,0.00001430683,0.001920856,0.00003343213,0.0001372405,0.9646571,0.001807224,0.0009724192,0.01168496,0.01029523],"study_design_scores_gemma":[0.0005229556,0.00006354473,0.8214754,0.00002076828,0.0001810486,0.00001114131,0.0001156198,0.1463163,0.00431221,0.0003137782,0.02609396,0.0005732453],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9599625,0.0001552307,0.002897763,0.00007811605,0.0001648635,0.00003274393,0.00002609799,0.000113752,0.03656897],"genre_scores_gemma":[0.9986346,0.00002076478,0.0003612905,0.00008585708,0.00005409928,0.000003432208,0.00004625744,0.00001479678,0.0007788457],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8183408,"threshold_uncertainty_score":0.6143218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006593362953253246,"score_gpt":0.2011021821494797,"score_spread":0.1945088191962264,"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."}}