{"id":"W1916026856","doi":"","title":"Wavelets application in acoustic emission signal detection of wire related events in pipeline","year":2008,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Ultrasonics and Acoustic Wave Propagation","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Short-time Fourier transform; Acoustic emission; Wavelet; Wavelet transform; Computer science; SIGNAL (programming language); Time–frequency analysis; Fast wavelet transform; Signal processing; Discrete wavelet transform; Fourier transform; Pipeline (software); Time domain; Acoustics; Pattern recognition (psychology); Electronic engineering; Artificial intelligence; Engineering; Computer vision; Fourier analysis; Mathematics; Digital signal processing; Telecommunications; Radar; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004143953,0.0004633987,0.0003402945,0.0009305652,0.0001611072,0.000373918,0.0002333814,0.0005104705,0.000673186],"category_scores_gemma":[0.0009922076,0.0001706951,0.000389879,0.00112849,0.0002826723,0.0005177761,0.0003326566,0.0003873317,0.0003325573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001182639,"about_ca_system_score_gemma":0.000202551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006101974,"about_ca_topic_score_gemma":0.0004584145,"domain_scores_codex":[0.9997502,0.00004085247,0.00001586318,0.00006192015,0.0001073506,0.00002380305],"domain_scores_gemma":[0.9996976,0.0001097533,0.00005128951,0.00002831239,0.00009672217,0.00001643437],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005255054,0.0001236761,0.007078952,0.0003724418,0.00006003432,0.0011635,0.0004964685,0.05938601,0.4273482,0.006253564,0.002214238,0.4949775],"study_design_scores_gemma":[0.0000246784,0.0003574599,0.01152228,0.00003648783,0.00006394892,0.0009760055,0.0002476184,0.8297845,0.1461478,0.003413199,0.007382289,0.00004372451],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.144734,0.0007693607,0.8514121,0.0001679834,0.0000745045,0.00002605222,0.000123174,0.0006302203,0.002062597],"genre_scores_gemma":[0.7156455,0.001880011,0.2769831,0.00007512247,0.0001027273,0.00003746652,0.0002754946,0.0001284836,0.004872172],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009305652,"threshold_uncertainty_score":0.002251983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006018896143409787,"score_gpt":0.1814215555823608,"score_spread":0.175402659438951,"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."}}