{"id":"W2293731104","doi":"10.1007/s00170-016-8556-x","title":"Joint optimization of lot-sizing and maintenance policy for a partially observable two-unit system","year":2016,"lang":"en","type":"article","venue":"The International Journal of Advanced Manufacturing Technology","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Production (economics); Sizing; Computer science; Process (computing); Mathematical optimization; Statistic; Markov chain; Turbine; Markov decision process; Unit (ring theory); Reliability engineering; Operations research; Markov process; Engineering; Mathematics; Statistics; Economics","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":[0.00182773,0.001667109,0.002623377,0.0008162681,0.0005757512,0.001976512,0.001584724,0.002277134,0.003620633],"category_scores_gemma":[0.003790804,0.001443152,0.0008952633,0.0009498952,0.00125786,0.001225264,0.001040588,0.001256124,0.0003370611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001753032,"about_ca_system_score_gemma":0.002442614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01969658,"about_ca_topic_score_gemma":0.01306403,"domain_scores_codex":[0.9992749,0.0002471804,0.00003573811,0.0001561075,0.000102051,0.0001839726],"domain_scores_gemma":[0.9970911,0.001884881,0.0004110402,0.0001038489,0.0002942106,0.0002150188],"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":[0.000107223,0.00002322571,0.0001967807,0.00003529575,0.00002588187,0.0000394811,0.00001034309,0.9973211,0.0003693806,0.0005276526,0.000122001,0.001221595],"study_design_scores_gemma":[0.00001660388,0.00002870363,0.0001722274,0.000001730379,0.000009796178,0.000003976151,0.000004206619,0.9993076,0.00008355389,0.0003423071,0.00002534056,0.000003816097],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4497624,0.001298068,0.5365751,0.001527106,0.0001597956,0.0002958862,0.001077983,0.0008962358,0.008407457],"genre_scores_gemma":[0.9894188,0.0001064064,0.008089513,0.00003717184,0.00002456412,0.00006635178,0.00013552,0.00003091965,0.002090844],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01969658,"threshold_uncertainty_score":0.03916383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01090804736955163,"score_gpt":0.2306198700149611,"score_spread":0.2197118226454095,"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."}}