{"id":"W4237543162","doi":"10.1155/2013/598490","title":"Fault Identification of Gearbox Degradation with Optimized Wavelet Neural Network","year":2013,"lang":"en","type":"article","venue":"Shock and Vibration","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Program for New Century Excellent Talents in University; National Natural Science Foundation of China; University of Alberta; Hubei Provincial Department of Education","keywords":"Morlet wavelet; Wavelet; Vibration; Artificial neural network; Fault (geology); Degradation (telecommunications); Acceleration; SIGNAL (programming language); Engineering; Structural engineering; Computer science; Pattern recognition (psychology); Wavelet transform; Artificial intelligence; Acoustics; Electronic engineering; Discrete wavelet transform; Geology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.00007389554,0.00008587902,0.0001016723,0.00004561163,0.00003777431,0.0000494306,0.0000432543,0.00004849017,0.00002625005],"category_scores_gemma":[0.00001189633,0.00007365125,0.00001397851,0.000115524,0.00001552649,0.0003119705,0.000008935914,0.00005820545,0.000003156729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001176973,"about_ca_system_score_gemma":0.000003909325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004539959,"about_ca_topic_score_gemma":0.00001877393,"domain_scores_codex":[0.9994917,0.00002000093,0.0002047087,0.00009901479,0.00009131288,0.00009328863],"domain_scores_gemma":[0.9997222,0.00002706338,0.00005485936,0.0001176123,0.00005160665,0.00002664839],"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":[0.00008325768,0.0001205062,0.01548736,0.0004152839,0.000130885,0.000001327004,0.0008946956,0.5208919,0.2897231,0.004666398,0.01383575,0.1537495],"study_design_scores_gemma":[0.000228596,0.00005090434,0.02375532,0.00002052863,0.00001436126,0.000001981837,0.00001995439,0.9157331,0.05954146,0.0004646241,0.00005789292,0.0001112788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8914855,0.00009453063,0.1070931,0.0001378656,0.00006008241,0.0004248608,0.000003039738,0.0002537735,0.0004472428],"genre_scores_gemma":[0.9885226,0.00006097943,0.01112853,0.00002548334,0.00005140435,0.00009181134,0.00007645487,0.00001532599,0.00002735588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3948412,"threshold_uncertainty_score":0.3003411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005736832888502585,"score_gpt":0.2205907204378937,"score_spread":0.2148538875493911,"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."}}