{"id":"W1989094992","doi":"10.1115/detc2009-86797","title":"Vibration-Based Fault Diagnosis of Slurry Pumps Using the Neighborhood Rough Set Model","year":2009,"lang":"en","type":"article","venue":"","topic":"Oil and Gas Production Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Syncrude","keywords":"Rough set; Impeller; Feature (linguistics); Fault (geology); Set (abstract data type); Pattern recognition (psychology); Dependency (UML); Computer science; Feature selection; Vibration; Artificial intelligence; Data mining; Mathematics; Engineering; Geology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.00007102602,0.00009552742,0.00009867655,0.00004535248,0.00005403213,0.00001956351,0.00009827614,0.00005161394,0.00005868165],"category_scores_gemma":[0.00001577679,0.00006906199,0.00004908106,0.0001592193,0.00001682438,0.0001567179,0.000006019964,0.00008092134,0.000001960812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002083987,"about_ca_system_score_gemma":0.00001501298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002631007,"about_ca_topic_score_gemma":0.000003257491,"domain_scores_codex":[0.9994958,0.00001115558,0.0001723052,0.0001000357,0.0001098851,0.000110794],"domain_scores_gemma":[0.9996579,0.00002448491,0.00002489391,0.0002246477,0.00004559573,0.00002247205],"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":[0.000002540947,0.00002583814,0.0001708194,0.00001413794,0.000008610377,2.17328e-7,0.0001354613,0.9833452,0.003093401,0.0006852272,0.003179481,0.009339119],"study_design_scores_gemma":[0.00005562792,0.0000177408,0.00008690201,0.000008893065,0.000009105345,5.502595e-7,0.00001847295,0.698196,0.2991187,0.002299136,0.0001182054,0.00007073014],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2066755,0.0004248386,0.7720215,0.004125969,0.0002373529,0.0004193313,0.00003301117,0.001633501,0.01442894],"genre_scores_gemma":[0.9867516,0.00003679312,0.01269159,0.0003653946,0.00005821858,0.00001328764,0.000004701689,0.00001171088,0.00006672474],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7800761,"threshold_uncertainty_score":0.2816266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02328119730359256,"score_gpt":0.2528752075900265,"score_spread":0.2295940102864339,"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."}}