{"id":"W2040645736","doi":"10.5539/cis.v6n3p118","title":"Application of Wavelet Transform Analysis to ADCs Harmonics Distortion","year":2013,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Harmonic wavelet transform; Computer science; Wavelet transform; Wavelet; Total harmonic distortion; Distortion (music); Harmonics; Discrete wavelet transform; Fourier transform; Algorithm; Harmonic; Computation; Second-generation wavelet transform; Stationary wavelet transform; Constant Q transform; Power (physics); Mathematics; Artificial intelligence; Acoustics; Telecommunications; Physics; Electrical engineering; Mathematical analysis; Engineering","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":[0.0001486591,0.00004956559,0.00007752144,0.0003443694,0.000038537,0.00006594975,0.0001343524,0.00001706236,0.000007387794],"category_scores_gemma":[0.000005876629,0.00004503363,0.0000200092,0.0009177024,0.0000365471,0.002416127,0.00002178099,0.00002911417,0.00001548066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002886261,"about_ca_system_score_gemma":0.000006103557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003165727,"about_ca_topic_score_gemma":0.000001789355,"domain_scores_codex":[0.9994977,0.000001877628,0.0002055876,0.00005724949,0.0001560911,0.00008149548],"domain_scores_gemma":[0.9996676,0.000009797407,0.00002820548,0.0001259743,0.0001109286,0.00005742866],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[7.187979e-7,0.00001088729,0.002534052,0.00004737028,0.00001482731,9.212925e-9,0.001885192,0.01716783,0.0009356349,0.001438192,0.001003708,0.9749616],"study_design_scores_gemma":[0.00002990915,0.00001969196,0.104034,0.00000290173,0.000007883898,3.109924e-7,0.000007835601,0.8854195,0.007765216,0.00006443975,0.002592061,0.00005622528],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1443426,0.00000509361,0.8541698,0.00006042258,0.00002734324,0.0001838576,0.000003311473,0.00009145,0.001116103],"genre_scores_gemma":[0.9797576,0.00002600603,0.02004662,0.0001101441,0.000006697538,0.00004050894,0.00001036067,0.000001396305,6.589288e-7],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9749054,"threshold_uncertainty_score":0.1836418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003600175828287202,"score_gpt":0.2317406264146335,"score_spread":0.2281404505863463,"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."}}