{"id":"W2322769727","doi":"10.1002/we.1934","title":"A stochastic power curve for wind turbines with reduced variability using conditional copula","year":2015,"lang":"en","type":"article","venue":"Wind Energy","topic":"Energy Load and Power Forecasting","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Turbine; Wind power; Wind speed; Copula (linguistics); Meteorology; Wind power forecasting; Wind profile power law; Environmental science; Econometrics; Statistics; Power (physics); Engineering; Mathematics; Electric power system; Geography; Physics; Aerospace engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001638532,0.0005465955,0.0005903707,0.0009060554,0.00028032,0.0007538577,0.0006990613,0.0004785992,0.001162829],"category_scores_gemma":[0.008041441,0.0003178883,0.0009570965,0.0009077236,0.0005104267,0.0008418887,0.0005454313,0.0009336041,0.0002330381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009253822,"about_ca_system_score_gemma":0.0009118471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01158733,"about_ca_topic_score_gemma":0.004887587,"domain_scores_codex":[0.999543,0.000183114,0.0000214879,0.00008471739,0.0001187374,0.00004906856],"domain_scores_gemma":[0.9973115,0.001719139,0.0003218145,0.0001790655,0.0004020802,0.00006645426],"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":[0.000007228606,0.000007973434,0.00115466,0.00001767102,0.00001427346,0.00006992938,0.00003667815,0.9800786,0.0007118709,0.009849724,0.000239209,0.007812204],"study_design_scores_gemma":[5.031147e-7,0.000002497802,0.0003308511,0.000001575458,0.00000147822,0.000009212527,0.000002392618,0.9982331,0.00007306808,0.001225612,0.0001170492,0.000002633597],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08972555,0.0001376305,0.907558,0.0001439382,0.00001142304,0.00003991322,0.0001518636,0.0002387303,0.001992846],"genre_scores_gemma":[0.9288342,0.0002389896,0.06874476,0.00002435962,0.00002154049,0.00006578548,0.0004998618,0.0001249011,0.001445549],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01158733,"threshold_uncertainty_score":0.02303976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02534918813565464,"score_gpt":0.2327827579722705,"score_spread":0.2074335698366158,"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."}}