{"id":"W2162084884","doi":"10.1109/pes.2008.4596924","title":"Adaptive active power line filter for interfacing wind-power DGs to distribution system","year":2008,"lang":"en","type":"article","venue":"","topic":"Power Quality and Harmonics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Electronic engineering; Harmonic; Computer science; Active filter; Adaptive filter; Noise (video); Power (physics); Wind power; Interfacing; Converters; Active noise control; Engineering; Filter (signal processing); Control theory (sociology); Electrical engineering; Voltage; Computer hardware","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":[0.0001225311,0.0001711074,0.0002117243,0.00004613669,0.00009205335,0.00001913006,0.0001196463,0.00009966625,0.00010248],"category_scores_gemma":[0.00003206188,0.0001614456,0.00009050853,0.000117632,0.00001921393,0.0001350048,0.00005688008,0.0001530307,0.000153859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002887831,"about_ca_system_score_gemma":0.00001986365,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001456528,"about_ca_topic_score_gemma":0.000008055415,"domain_scores_codex":[0.9991266,0.00001645528,0.0002387498,0.0001951698,0.0001314588,0.0002915449],"domain_scores_gemma":[0.9995094,0.00007256024,0.00002497411,0.0001862975,0.00009164611,0.0001151511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00490528,0.001027375,0.0002676758,0.001751798,0.003403415,0.0002413273,0.09453408,0.1422143,0.1314929,0.2466016,0.3614971,0.0120631],"study_design_scores_gemma":[0.00380098,0.002316832,0.003429479,0.0008096297,0.0001352627,0.0001641902,0.01347492,0.1682889,0.6782279,0.0005307589,0.1260938,0.002727298],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2610825,0.00005647747,0.7272982,0.0001637294,0.0006813144,0.0004980031,0.0004993022,0.0004368203,0.00928364],"genre_scores_gemma":[0.998252,0.000002216023,0.001013243,0.0001075134,0.00005649671,0.00003212649,0.00004440024,0.00002769408,0.0004643499],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7371694,"threshold_uncertainty_score":0.658356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03882540213973366,"score_gpt":0.2448736039271359,"score_spread":0.2060482017874023,"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."}}