{"id":"W2072599024","doi":"10.1006/mssp.2002.1507","title":"GEARBOX FAULT DIAGNOSIS USING ADAPTIVE WAVELET FILTER","year":2003,"lang":"en","type":"article","venue":"Mechanical Systems and Signal Processing","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":343,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Morlet wavelet; Wavelet; Discrete wavelet transform; Stationary wavelet transform; Second-generation wavelet transform; Wavelet packet decomposition; Wavelet transform; Lifting scheme; Computer science; Pattern recognition (psychology); Speech recognition; Mathematics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.000285377,0.0003362036,0.0004428282,0.00055793,0.0001824263,0.0003427944,0.0003448101,0.0005640059,0.000822763],"category_scores_gemma":[0.001268608,0.0001681487,0.0002713075,0.0003356907,0.0001539467,0.0005409623,0.0002457422,0.0003419754,0.0002098639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001530656,"about_ca_system_score_gemma":0.0001986557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007823712,"about_ca_topic_score_gemma":0.000894524,"domain_scores_codex":[0.9998595,0.00001926523,0.00001285265,0.00003161741,0.0000611632,0.00001567124],"domain_scores_gemma":[0.9995849,0.000210028,0.00004152477,0.00004006394,0.0001100521,0.00001352339],"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":[0.0009271954,0.0001417989,0.003474396,0.000183066,0.00008720197,0.0002790798,0.000100972,0.04991544,0.1774931,0.002839825,0.0008388496,0.7637191],"study_design_scores_gemma":[0.00004546407,0.0001842312,0.004724996,0.00001377581,0.00008716262,0.0002624008,0.00002729737,0.9358689,0.05638261,0.001473907,0.0009144317,0.00001483919],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1299629,0.0002757614,0.8681655,0.00007049658,0.00008468566,0.00002210761,0.00002663771,0.0004310927,0.0009608839],"genre_scores_gemma":[0.8655703,0.0002390803,0.1325699,0.00003904177,0.00004027932,0.00002808423,0.00005589862,0.00002417925,0.001433252],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.000822763,"threshold_uncertainty_score":0.002752364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02603872966837269,"score_gpt":0.2609630073227889,"score_spread":0.2349242776544162,"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."}}