{"id":"W2074668057","doi":"10.1115/detc2010-29126","title":"EMD, Ranking Mutual Information and PCA Based Condition Monitoring","year":2010,"lang":"en","type":"article","venue":"","topic":"Engineering Diagnostics and Reliability","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Syncrude","keywords":"Mutual information; Condition monitoring; Ranking (information retrieval); Monotonic function; Impeller; Data mining; Computer science; Artificial intelligence; Fault (geology); Pattern recognition (psychology); Feature (linguistics); Fault detection and isolation; Information fusion; Feature extraction; Machine learning; Engineering; Mathematics","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":[0.00009269148,0.00006867562,0.00005661001,0.00005646493,0.00003288144,0.00004596335,0.00003168376,0.0000669815,0.00003512645],"category_scores_gemma":[0.00006373688,0.00006462925,0.0000143389,0.00005101908,0.00001436658,0.0002174255,0.000007538315,0.0001513591,0.00001880195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001045295,"about_ca_system_score_gemma":0.000004508629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007641629,"about_ca_topic_score_gemma":0.000003269181,"domain_scores_codex":[0.9996736,0.000001969123,0.0001126015,0.00004429934,0.00006851237,0.00009903638],"domain_scores_gemma":[0.9997611,0.00007422538,0.000008328472,0.00008743588,0.00002440567,0.00004450596],"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":[0.00001811835,0.00007046195,0.1078212,0.00130811,0.00009162826,0.000007695489,0.001196335,0.5610125,0.2134216,0.01144621,0.002140408,0.1014657],"study_design_scores_gemma":[0.0005728684,0.00002311507,0.08003569,0.00003984252,0.00001344938,0.00000412623,0.00003714325,0.8507373,0.05785104,0.0002166999,0.01018823,0.0002804579],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9677256,0.00001858054,0.02876826,0.00002306244,0.00101429,0.00007291682,0.0000042771,0.000319787,0.00205327],"genre_scores_gemma":[0.9950105,0.00001556087,0.004839173,0.000009691961,0.00009244357,0.000008406032,0.00001212482,0.000007590132,0.000004507442],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2897248,"threshold_uncertainty_score":0.2635504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002361691469539282,"score_gpt":0.1825384536042161,"score_spread":0.1801767621346768,"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."}}