{"id":"W4415042415","doi":"10.3850/978-981-94-3281-3_esrel-sra-e2025-p6336-cd","title":"Tracking Reliability and Updating the Overhaul Interval of Engineering Components: Bayesian Approach","year":2025,"lang":"en","type":"article","venue":"","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; University Network of Excellence in Nuclear Engineering","keywords":"Interval (graph theory); Reliability (semiconductor); Tracking (education); Bayesian probability; Interval arithmetic; Interval estimation","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003209528,0.00009598595,0.0001458303,0.00004424215,0.00003690172,0.0000275678,0.0001055699,0.00004989741,0.000008243475],"category_scores_gemma":[0.0001097119,0.00007110312,0.00003885129,0.0001676228,0.00004349371,0.0001368602,0.00004677713,0.0001357045,2.552386e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003660696,"about_ca_system_score_gemma":0.000005148424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002432584,"about_ca_topic_score_gemma":0.000002021802,"domain_scores_codex":[0.9994045,0.00001451447,0.0002568408,0.0001298468,0.00006692614,0.0001273264],"domain_scores_gemma":[0.9996307,0.00008587278,0.00002068453,0.0002070044,0.0000382693,0.00001742199],"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":[0.000008877039,0.00003277033,0.002638105,0.0006031141,0.00003866387,1.592087e-7,0.00038683,0.9774498,0.002471955,0.01077699,0.0002122599,0.005380491],"study_design_scores_gemma":[0.0001404779,0.00000600979,0.006685252,0.0000734729,0.00001133841,0.000001140088,0.0002423361,0.9903268,0.001709769,0.0002598985,0.0004717997,0.00007175557],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.189544,0.0001264906,0.7927343,0.0001904363,0.0001849226,0.0002425662,0.000002094454,0.0001825042,0.01679268],"genre_scores_gemma":[0.9841918,0.00002870942,0.01566943,0.0000417978,0.0000112346,0.00001029947,0.000004178639,0.000009130445,0.00003337859],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7946478,"threshold_uncertainty_score":0.2899501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006391451037670458,"score_gpt":0.1973547199702028,"score_spread":0.1909632689325323,"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."}}