{"id":"W2062951546","doi":"10.1016/j.epsr.2011.02.003","title":"On the application of wavelet transform for symmetrical components computations in the presence of stationary and non-stationary power quality disturbances","year":2011,"lang":"en","type":"article","venue":"Electric Power Systems Research","topic":"Power Quality and Harmonics","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University; Ontario Tech University","funders":"","keywords":"Wavelet; Discrete wavelet transform; Wavelet transform; Daubechies wavelet; Electronic engineering; Wavelet packet decomposition; Stationary wavelet transform; Electric power system; Engineering; Second-generation wavelet transform; Control theory (sociology); Computer science; Power (physics); Artificial intelligence","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":[0.00300675,0.00009630885,0.0002023389,0.0002836004,0.0001146105,0.00001831762,0.0003423748,0.00006320071,0.000003750849],"category_scores_gemma":[0.0002144779,0.00006495194,0.00004197575,0.001046906,0.0001141636,0.0000983128,0.00001489384,0.0002835685,0.000002359486],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006018401,"about_ca_system_score_gemma":0.00005217519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003344153,"about_ca_topic_score_gemma":0.00001518433,"domain_scores_codex":[0.9980135,0.0004046886,0.000493227,0.0001669257,0.0006582836,0.0002633927],"domain_scores_gemma":[0.9954395,0.003981132,0.00007438882,0.0002449673,0.0002239611,0.00003600629],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.001192732,0.002401505,0.004053964,0.003126113,0.0004376092,0.000006494311,0.08606987,0.004449561,0.009507512,0.8670307,0.01152961,0.01019436],"study_design_scores_gemma":[0.001956315,0.001441151,0.4860503,0.000266238,0.00002472749,0.00001153719,0.00751087,0.460753,0.005074264,0.0329956,0.00340847,0.000507555],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7602466,0.002257304,0.227479,0.0004468674,0.0001450062,0.003386309,0.0002359308,0.00003220698,0.005770874],"genre_scores_gemma":[0.9994069,0.00007395518,0.0001171811,0.00001176265,0.000006673477,0.00032822,0.0000253438,0.00001094602,0.00001904912],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8340351,"threshold_uncertainty_score":0.2648663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1128332825408253,"score_gpt":0.3515220100772416,"score_spread":0.2386887275364163,"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."}}