{"id":"W3145225624","doi":"10.1109/tpwrd.2007.899776","title":"Reformulating Three-Phase Power Components Definitions Contained in the IEEE Standard 1459–2000 Using Discrete Wavelet Transform","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Power Delivery","topic":"Power Quality and Harmonics","field":"Engineering","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Discrete wavelet transform; Second-generation wavelet transform; Wavelet; Wavelet transform; Discrete Fourier transform (general); Harmonic wavelet transform; Stationary wavelet transform; Frequency domain; Algorithm; Wavelet packet decomposition; Electronic engineering; Lifting scheme; Computer science; Mathematics; Fourier transform; Fractional Fourier transform; Fourier analysis; Engineering; Artificial intelligence; Mathematical analysis","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008574596,0.0003809957,0.0003725677,0.0003647198,0.0004203561,0.00009042118,0.0002978589,0.0002178608,0.0001854815],"category_scores_gemma":[0.000003826628,0.0003356246,0.0002665696,0.0005251687,0.0001039204,0.0004885045,0.000001284155,0.000858368,0.00003797989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005826356,"about_ca_system_score_gemma":0.00007463025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001857612,"about_ca_topic_score_gemma":0.0008533644,"domain_scores_codex":[0.9976069,0.00006950435,0.0007728598,0.0003048169,0.0005246483,0.0007213237],"domain_scores_gemma":[0.9989831,0.0002915715,0.00006180622,0.0004408029,0.00007275316,0.0001499123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.009988262,0.00570567,0.0001719821,0.0007305592,0.002651316,0.001976797,0.1017084,0.6224188,0.1810251,0.006700541,0.0009110082,0.06601164],"study_design_scores_gemma":[0.04979466,0.004873578,0.004138072,0.002709981,0.001556766,0.0009533794,0.0205675,0.6359693,0.2377969,0.009161646,0.02355489,0.0089233],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4626077,0.00007653327,0.5333424,0.00008541821,0.0006030217,0.0003397629,0.0003811716,0.0001665026,0.00239757],"genre_scores_gemma":[0.9981774,0.00008158359,0.001264124,0.0003252665,0.00002597547,0.00002089813,0.00002160274,0.00006779991,0.00001534553],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5355697,"threshold_uncertainty_score":0.9999096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05810877269198259,"score_gpt":0.2851902608597501,"score_spread":0.2270814881677675,"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."}}