{"id":"W1968582355","doi":"10.1088/0964-1726/20/4/045016","title":"Separation of the vibration-induced signal of oil debris for vibration monitoring","year":2011,"lang":"en","type":"article","venue":"Smart Materials and Structures","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Vibration; SIGNAL (programming language); Debris; Condition monitoring; Acoustics; Interference (communication); Particle (ecology); Wavelet; Structural engineering; Computer science; Materials science; Engineering; Geology; Physics; Artificial intelligence; Electrical engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002665874,0.0004749971,0.0004571131,0.0005489615,0.0001935692,0.0003661877,0.0004104539,0.0006270981,0.001342597],"category_scores_gemma":[0.000928976,0.0001550733,0.0003346654,0.0003988586,0.0003737735,0.000598166,0.0003373824,0.0004890052,0.0005456351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001804929,"about_ca_system_score_gemma":0.000334733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002155423,"about_ca_topic_score_gemma":0.0004297647,"domain_scores_codex":[0.9997568,0.00002856963,0.00001267303,0.00004101303,0.0001397346,0.00002133028],"domain_scores_gemma":[0.9995677,0.0001445479,0.00007525218,0.00005110776,0.0001316183,0.0000297202],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002380345,0.0000945808,0.001158669,0.0001464192,0.00001651702,0.0001150781,0.0000593886,0.004293512,0.9062595,0.0009809295,0.0001761235,0.08646126],"study_design_scores_gemma":[0.00004606144,0.0006660481,0.006207899,0.00003099833,0.00005522589,0.0005520995,0.00008863102,0.1652727,0.8210675,0.001521064,0.00444652,0.00004523506],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2915303,0.0008667106,0.7053567,0.0001947173,0.0001207879,0.00006183433,0.00006273051,0.0004181842,0.001387981],"genre_scores_gemma":[0.7834193,0.0004814559,0.2137412,0.00006161795,0.00004705451,0.00006492432,0.0001444539,0.00005867214,0.001981372],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001342597,"threshold_uncertainty_score":0.004491448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01920930850293391,"score_gpt":0.267592387110243,"score_spread":0.248383078607309,"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."}}