{"id":"W2540446840","doi":"10.1109/epc.2007.4520339","title":"New Generation of Signal processing Techniques for Power System Applications","year":2007,"lang":"en","type":"article","venue":"","topic":"Power Quality and Harmonics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; SIGNAL (programming language); Signal processing; Power (physics); Electronic engineering; Noise (video); Electric power system; Digital signal processing; Engineering; Computer hardware; Artificial intelligence; Physics","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":[0.0001853588,0.00004446274,0.00006372569,0.00003781836,0.00002654223,0.00001091172,0.00004563958,0.00004644664,0.00001169356],"category_scores_gemma":[0.000001026665,0.0000437084,0.00002268465,0.00006982926,0.000004748684,0.00006125197,0.000003501653,0.00002701391,0.000002018481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003235817,"about_ca_system_score_gemma":0.0000179968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004441029,"about_ca_topic_score_gemma":0.000007668431,"domain_scores_codex":[0.9996406,0.000001746472,0.0001673271,0.00005384729,0.00005294086,0.00008353563],"domain_scores_gemma":[0.9998322,0.00001395636,0.00002058236,0.0000620329,0.00004167335,0.000029566],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001073291,0.00003190372,0.00002380852,0.0009602773,0.00003135999,2.746255e-7,0.0006516791,0.0007936594,0.4769636,0.1554149,0.007503095,0.3576146],"study_design_scores_gemma":[0.00009698218,0.00002356104,0.00002374372,0.00003109974,0.00001207095,0.000002108823,0.0001730563,0.0387917,0.9082971,0.0002412016,0.05219174,0.0001156223],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0005971041,0.0001861709,0.9872259,0.00001322847,0.00001903236,0.0002517006,0.000003509882,0.0003276832,0.01137566],"genre_scores_gemma":[0.8727039,0.000002057761,0.1270015,0.00001392235,0.00009455354,0.00002920728,0.00000729011,0.00000992126,0.0001376828],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8721068,"threshold_uncertainty_score":0.1782377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03796798764387553,"score_gpt":0.2839378735572926,"score_spread":0.245969885913417,"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."}}