{"id":"W2105647959","doi":"10.1108/jqme-12-2012-0047","title":"Risk-based maintenance and remaining life assessment for gas turbines","year":2015,"lang":"en","type":"article","venue":"Journal of Quality in Maintenance Engineering","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; Nalcor Energy (Canada)","funders":"","keywords":"Reliability engineering; Weibull distribution; Risk analysis (engineering); Engineering; Preventive maintenance; Gas turbines; Risk assessment; Interval (graph theory); Risk management; Work (physics); Turbine; Operations research; Operations management; Computer science; Business; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003908409,0.0002539398,0.0005767094,0.0002487517,0.00003460744,0.00006180764,0.0001995204,0.0001235187,0.000002330481],"category_scores_gemma":[0.004048458,0.0002268621,0.0001327748,0.0002784089,0.00004994398,0.0003858707,0.00002352123,0.0005024068,5.913187e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003992364,"about_ca_system_score_gemma":0.000143243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001719052,"about_ca_topic_score_gemma":0.00001567446,"domain_scores_codex":[0.9979272,0.00007436292,0.001048062,0.0001900044,0.0002996972,0.0004606861],"domain_scores_gemma":[0.9982949,0.0004477355,0.0003312213,0.0002182022,0.0004393664,0.000268544],"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":[0.00009281281,0.00003052182,0.003558453,0.0002813929,0.00003403782,0.000009184087,0.0003507359,0.9914533,0.0004221183,0.001594443,0.0009191317,0.00125382],"study_design_scores_gemma":[0.002961023,0.0001892388,0.009899398,0.0006435407,0.00002810664,0.00002735287,0.0007512593,0.9799896,0.0002230671,0.001916334,0.003004645,0.0003663602],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2525952,0.0005239084,0.7446368,0.0008509219,0.0008633524,0.0002780662,0.00001457128,0.00008556097,0.0001516102],"genre_scores_gemma":[0.86339,0.0003683214,0.1358286,0.0001187393,0.0001983235,0.00002726603,0.000003408119,0.00004785529,0.00001741212],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6107948,"threshold_uncertainty_score":0.9251168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02507879782168979,"score_gpt":0.2849343116025848,"score_spread":0.2598555137808949,"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."}}