{"id":"W1888601734","doi":"10.1109/ccece.2008.4564768","title":"Implementation of the linear digital filter for extracting stationary power quality disturbances","year":2008,"lang":"en","type":"article","venue":"Conference proceedings - Canadian Conference on Electrical and Computer Engineering","topic":"Power Quality and Harmonics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Harmonics; Flicker; Voltage; Computer science; Control theory (sociology); Voltage optimisation; Swell; Electronic engineering; Power (physics); Switched-mode power supply; Engineering; Electrical engineering; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009371528,0.0001890585,0.0002127178,0.0001048087,0.000131938,0.00008821332,0.0002006815,0.00007594542,0.00001960112],"category_scores_gemma":[0.00002643718,0.0001666681,0.00005979732,0.0001869219,0.00004652775,0.000284672,0.00002129483,0.0002261888,0.000001410715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008130207,"about_ca_system_score_gemma":0.0001799921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003228522,"about_ca_topic_score_gemma":0.0002041394,"domain_scores_codex":[0.9989346,0.00000438704,0.0003119044,0.0002180293,0.0001651583,0.0003659583],"domain_scores_gemma":[0.9994138,0.0000859109,0.00006213767,0.00007785798,0.0001789507,0.0001813107],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001574825,0.0002336026,0.09541422,0.001808919,0.0007890454,0.00001999837,0.02323599,0.00608356,0.01278147,0.6459561,0.006569029,0.2069505],"study_design_scores_gemma":[0.0007342921,0.0003002448,0.150606,0.0001575562,0.00002547466,0.00003426584,0.0003475444,0.8365793,0.004138875,0.001229949,0.005090895,0.0007556612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9367312,0.0001199393,0.06095739,0.0004466225,0.000273318,0.0004174991,0.0001356728,0.000128995,0.000789369],"genre_scores_gemma":[0.9989607,0.00004302254,0.0007631842,0.0000799316,0.00006551137,0.00003156599,0.00001141413,0.00001709128,0.00002760891],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8304957,"threshold_uncertainty_score":0.6796529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03786014780428345,"score_gpt":0.2527593880633514,"score_spread":0.2148992402590679,"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."}}