{"id":"W2132911706","doi":"10.1109/tec.2006.889605","title":"Macromodel of Spatial Smoothing in Wind Farms","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Energy Conversion","topic":"Wind Energy Research and Development","field":"Engineering","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Smoothing; Wind power; Turbine; Traverse; Aerodynamics; Wind speed; Harmonic; Harmonics; Power (physics); Control theory (sociology); Mathematics; Computer science; Engineering; Meteorology; Aerospace engineering; Electrical engineering; Physics; Acoustics; Statistics; Geology; Geodesy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000161333,0.0001157693,0.0001314063,0.0003500214,0.00004297862,0.00000648005,0.00009697059,0.00010191,0.0001097767],"category_scores_gemma":[0.000001124519,0.0001196449,0.00005591162,0.0002204062,0.00002907352,0.00009727997,0.000001075614,0.000167475,0.00001115736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001351441,"about_ca_system_score_gemma":0.00002794816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008039387,"about_ca_topic_score_gemma":0.0005893478,"domain_scores_codex":[0.9991166,0.00001348596,0.0002213988,0.0001347868,0.0002334926,0.0002802173],"domain_scores_gemma":[0.9996818,0.00005133289,0.00001549524,0.0001292077,0.00002555418,0.00009659978],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001721477,0.0001145631,0.0001764874,0.00004410437,0.00004328102,0.00004066111,0.0003629896,0.8825127,0.02805657,0.00004849784,0.00007331093,0.08835472],"study_design_scores_gemma":[0.001134563,0.00008580877,0.001344501,0.00007459889,0.000006461369,0.000005181231,0.0001348158,0.08828712,0.9064304,0.00006391002,0.002197146,0.0002354619],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3478318,0.00002147025,0.6497968,0.00001900627,0.000384634,0.00002698597,0.000003212004,0.00005990386,0.001856164],"genre_scores_gemma":[0.9991184,0.00009694818,0.0004871632,0.0000287102,0.00002126774,0.000002511615,0.000003307344,0.00001935028,0.0002223424],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8783739,"threshold_uncertainty_score":0.4878976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009016311177778865,"score_gpt":0.2087297930816883,"score_spread":0.1997134819039095,"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."}}