{"id":"W7117121194","doi":"10.18280/jesa.581120","title":"Robust Bearing Fault Detection and Classification Using Deep Neural Networks: A Comprehensive Study on the CWRU Dataset","year":2025,"lang":"","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Bearing (navigation); Pattern recognition (psychology); Artificial neural network; Deep learning; Fault detection and isolation; Support vector machine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00141903,0.002095979,0.001639986,0.002022108,0.0006030797,0.0008436125,0.002280621,0.001539167,0.00192453],"category_scores_gemma":[0.002886855,0.0003100809,0.001070495,0.001680542,0.0006157755,0.0009956354,0.001153644,0.001184786,0.001658548],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008610807,"about_ca_system_score_gemma":0.001490834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02890852,"about_ca_topic_score_gemma":0.04304663,"domain_scores_codex":[0.998744,0.0001608383,0.0001051826,0.0002945527,0.0005100862,0.0001854623],"domain_scores_gemma":[0.9986115,0.000301812,0.0001220404,0.0003829759,0.0004964216,0.0000853458],"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":[0.002633775,0.003511248,0.02808348,0.001905648,0.001228034,0.001476226,0.0002255883,0.1074382,0.03048787,0.001778297,0.282647,0.5385847],"study_design_scores_gemma":[0.0006685384,0.001788049,0.08794768,0.0003832695,0.0007223011,0.001555677,0.0007298423,0.7487972,0.05522862,0.003329693,0.09858091,0.0002682091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8432073,0.009619732,0.03528334,0.001450342,0.001277855,0.000440465,0.08713204,0.0119446,0.009644263],"genre_scores_gemma":[0.5533856,0.002019144,0.03622402,0.0003856221,0.0002460682,0.0002130247,0.3960027,0.000612534,0.01091127],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02890852,"threshold_uncertainty_score":0.05748051,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05094348344256894,"score_gpt":0.3083002343155921,"score_spread":0.2573567508730231,"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."}}