{"id":"W2548568551","doi":"","title":"Availability optimization model for stochastically degrading systems under preventive replacement and minimal repair","year":2013,"lang":"en","type":"article","venue":"Industrial Engineering and Systems Management (IESM), Proceedings of 2013 International Conference on","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Preventive maintenance; Optimization problem; Reliability engineering; Mathematical optimization; Condition-based maintenance; Weibull distribution; Stochastic optimization; Computer science; Engineering; Mathematics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001605719,0.001392288,0.00159371,0.0008940788,0.0004572904,0.001534327,0.001674676,0.001848613,0.002617823],"category_scores_gemma":[0.002927116,0.0008000024,0.001106031,0.0008772488,0.0008865188,0.0009993869,0.0009221613,0.001307299,0.0003792106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001556281,"about_ca_system_score_gemma":0.001209064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008895562,"about_ca_topic_score_gemma":0.004123798,"domain_scores_codex":[0.9989299,0.0003395802,0.00005558169,0.0002404111,0.0002350768,0.0001994063],"domain_scores_gemma":[0.9981855,0.001007261,0.0004033466,0.00005044316,0.0002716546,0.00008182667],"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":[0.00002842292,0.00001577543,0.0002016921,0.00003925616,0.00001912734,0.00008344424,0.00002654852,0.9925915,0.0005871693,0.004797977,0.0001900776,0.001419154],"study_design_scores_gemma":[0.000005750607,0.00001649989,0.0001266402,0.000003036313,0.000007234736,0.00001270035,0.000005951938,0.9983686,0.00006714,0.001258023,0.0001248204,0.000003610763],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08488488,0.001778836,0.8992103,0.001092698,0.0001001796,0.0001145598,0.000544655,0.0003135568,0.01196036],"genre_scores_gemma":[0.9640138,0.0008981907,0.02416457,0.0001228701,0.00006288739,0.0002261705,0.0002704489,0.00006221973,0.01017882],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008895562,"threshold_uncertainty_score":0.01768762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03670418675889726,"score_gpt":0.2265399704429923,"score_spread":0.189835783684095,"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."}}