{"id":"W2141232848","doi":"10.1109/ccece.1998.685616","title":"Application of wavelets for power system transient analysis","year":2002,"lang":"en","type":"article","venue":"","topic":"Power Quality and Harmonics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Wavelet; Transient (computer programming); Wavelet transform; Transient analysis; Electric power system; Computer science; Power (physics); Multiresolution analysis; Electronic engineering; Discrete wavelet transform; Transient response; Artificial intelligence; Engineering; Electrical engineering; 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":[0.00007500326,0.00004436745,0.0001196964,0.00006061028,0.00001116072,0.000003697563,0.00004877332,0.00003298065,0.00006226423],"category_scores_gemma":[0.000001384115,0.00004205297,0.00009593926,0.000187321,0.000005112306,0.00002411688,0.000001644724,0.00001944386,0.00001382725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002168932,"about_ca_system_score_gemma":6.65132e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005453505,"about_ca_topic_score_gemma":0.000006583528,"domain_scores_codex":[0.9996393,0.000003846927,0.00015244,0.00006211537,0.00005946506,0.00008288882],"domain_scores_gemma":[0.999792,0.00001907499,0.0000133657,0.0001304403,0.00002156097,0.00002353166],"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":[0.00004956654,0.0006536961,0.0008654338,0.004999601,0.007695965,0.000003056658,0.01566237,0.3483873,0.07423723,0.4651911,0.02162206,0.06063262],"study_design_scores_gemma":[0.0001356478,0.00001153236,0.0004907005,0.000003287253,0.0001500693,3.333289e-7,0.0001153454,0.9813429,0.005599038,0.00001419325,0.01206454,0.00007244457],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02548581,0.0001509607,0.9605527,0.0000413072,0.00003845779,0.0001402889,0.00002232934,0.000132741,0.01343544],"genre_scores_gemma":[0.99844,0.00000751323,0.001399281,0.00001107205,0.000005891716,0.00002208023,0.000006164313,0.000005992901,0.0001019889],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9729542,"threshold_uncertainty_score":0.171487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01838064399199088,"score_gpt":0.2156697970713347,"score_spread":0.1972891530793438,"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."}}