{"id":"W4233512660","doi":"10.1002/9780470061596.risk0502","title":"Condition Monitoring","year":2008,"lang":"en","type":"other","venue":"Encyclopedia of Quantitative Risk Analysis and Assessment","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Condition monitoring; Fault (geology); Predictive maintenance; Condition-based maintenance; Data acquisition; Preventive maintenance; Computer science; Reliability engineering; Fault detection and isolation; Noise (video); Engineering; 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":[0.001192594,0.001343332,0.0008331775,0.003606339,0.0009548655,0.002732155,0.001790131,0.001175627,0.09599851],"category_scores_gemma":[0.004447265,0.0003128761,0.0004592155,0.002484539,0.0003775454,0.002542552,0.001718898,0.0009728168,0.04408323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001003507,"about_ca_system_score_gemma":0.0009721604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0029944,"about_ca_topic_score_gemma":0.001791606,"domain_scores_codex":[0.99752,0.0002223143,0.000132833,0.0006799329,0.001297232,0.0001476556],"domain_scores_gemma":[0.9966157,0.000383957,0.0002437831,0.0006602147,0.001972357,0.0001239386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005496305,0.0001538891,0.00736824,0.0006037535,0.00004201893,0.0002803185,0.0003286965,0.002895544,0.01873842,0.0103797,0.161349,0.7973109],"study_design_scores_gemma":[0.00008092621,0.0003614996,0.01546119,0.0004450624,0.0001028573,0.000848544,0.0003631206,0.02274377,0.05047343,0.007443653,0.9015145,0.0001613364],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[0.03452253,0.004250353,0.2645733,0.001964466,0.003388583,0.001977935,0.02610654,0.04354421,0.6196721],"genre_scores_gemma":[0.4240136,0.003745334,0.1235288,0.002514082,0.001153622,0.001258112,0.03086134,0.002910227,0.4100149],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.09599851,"threshold_uncertainty_score":0.321147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01181233461315601,"score_gpt":0.3381826292104562,"score_spread":0.3263702945973002,"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."}}