{"id":"W2235046371","doi":"10.1139/tcsme-2013-0094","title":"PROPOSING A NEW ACOUSTIC EMISSION PARAMETER FOR BEARING CONDITION MONITORING IN ROTATING MACHINES","year":2013,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"École de technologie supérieure","keywords":"Bearing (navigation); Rotational speed; Acoustic emission; Process (computing); Condition monitoring; Work (physics); Standard deviation; Acoustics; Rolling-element bearing; Computer science; Structural engineering; Mechanical engineering; Engineering; Vibration; Physics; Mathematics; Statistics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001619073,0.0001862241,0.0002173483,0.00009642485,0.0001473907,0.00004873201,0.0002116749,0.0001701125,0.00001586186],"category_scores_gemma":[0.0001172285,0.0001776157,0.0003502984,0.0002326339,0.00001219443,0.0002040899,0.000005802343,0.0002942547,4.019701e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000383478,"about_ca_system_score_gemma":0.00007294072,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009916176,"about_ca_topic_score_gemma":0.004079376,"domain_scores_codex":[0.9989961,0.000005909308,0.0003267622,0.0001675705,0.0001108929,0.000392756],"domain_scores_gemma":[0.9992978,0.0002477721,0.00003595844,0.0001877673,0.00004573583,0.0001849526],"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":[0.000003890395,0.00002078113,0.0001899322,0.0008470492,0.0001246358,1.972292e-7,0.0005480121,0.7209756,0.2494328,0.0001882547,0.0005125791,0.02715627],"study_design_scores_gemma":[0.0003130386,0.00002817535,0.0002269514,0.0003417004,0.00004722521,0.000002261394,0.00003995787,0.8857591,0.112261,0.000664603,0.000123234,0.0001928154],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1857848,0.0000945557,0.8114713,0.000249835,0.000433999,0.001646663,0.00004482236,0.0002638868,0.00001010179],"genre_scores_gemma":[0.8783395,0.000008541126,0.1209217,0.00001825177,0.00007102304,0.0005439736,0.000005329781,0.00006392689,0.00002773977],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6925548,"threshold_uncertainty_score":0.9966769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01085672077702987,"score_gpt":0.2505654410917344,"score_spread":0.2397087203147045,"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."}}