{"id":"W1568005484","doi":"10.1109/icnn.1995.488078","title":"Vibration fault detection of large turbogenerators using neural networks","year":2002,"lang":"en","type":"article","venue":"","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Bruce Power","keywords":"Vibration; Computer science; Artificial neural network; Fault detection and isolation; Fault (geology); Control engineering; Control theory (sociology); Acoustics; Artificial intelligence; Engineering; Physics; Geology; Control (management); Actuator; Seismology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002621638,0.0003932266,0.0002106164,0.0002826182,0.0001105221,0.0001956713,0.0002127419,0.0003470459,0.0003222718],"category_scores_gemma":[0.0009270757,0.0001424771,0.0001082119,0.0001447087,0.000148688,0.000301034,0.000120982,0.0002380398,0.00009561921],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000260655,"about_ca_system_score_gemma":0.0001342124,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001708519,"about_ca_topic_score_gemma":0.002218092,"domain_scores_codex":[0.9999058,0.00002186941,0.000006083476,0.00002454252,0.00002879802,0.00001287787],"domain_scores_gemma":[0.9996316,0.0001869963,0.00006361611,0.00001832243,0.00008782012,0.00001152917],"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":[0.0009207966,0.00024095,0.01395715,0.0001405345,0.00007328482,0.0003068511,0.0001473896,0.3331611,0.2091864,0.00037668,0.000741855,0.4407471],"study_design_scores_gemma":[0.00001216781,0.0001577566,0.007678633,0.000005313264,0.00001218498,0.00004694207,0.00001742411,0.969157,0.02248131,0.0002362122,0.000186994,0.000008038865],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8763981,0.0002521792,0.1219287,0.000110657,0.00002975533,0.00001942886,0.00004173513,0.000525939,0.0006936479],"genre_scores_gemma":[0.9881393,0.00004528385,0.01133002,0.00000782242,0.000006954751,0.000006653538,0.00003166494,0.000004379455,0.0004279793],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001708519,"threshold_uncertainty_score":0.003397107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01205275983878863,"score_gpt":0.2474650161734203,"score_spread":0.2354122563346317,"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."}}