{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002987298,0.0001162076,0.0002221905,0.0002859015,0.00004032704,0.00001716394,0.0003884371,0.00006890588,0.000003845198],"category_scores_gemma":[0.0003068921,0.00007227059,0.00006436938,0.00008041417,0.0001107841,0.0002696647,0.00007221972,0.0001086934,5.470966e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001906178,"about_ca_system_score_gemma":0.00003816507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000622692,"about_ca_topic_score_gemma":0.000006990791,"domain_scores_codex":[0.9990621,0.00001237431,0.0004855458,0.0001019909,0.0001582418,0.0001797288],"domain_scores_gemma":[0.9990137,0.0001164994,0.0003242083,0.000166336,0.0003497134,0.00002954608],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001186466,0.00001079035,0.00003606926,0.00005601363,0.00008657425,0.000003429126,0.00004914768,0.9263272,0.03532887,0.01149336,0.00002747785,0.02646241],"study_design_scores_gemma":[0.003279685,0.0002470688,0.0002854339,0.001292654,0.0000457493,0.0003803768,0.0005762178,0.08580209,0.8829633,0.02217966,0.002707397,0.0002403367],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2926138,0.0001718404,0.7021162,0.004189829,0.0004774338,0.0001960215,0.00001174549,0.0001020781,0.0001210097],"genre_scores_gemma":[0.945872,0.0007854718,0.05312959,0.00002922315,0.0001068312,0.00001494729,9.160213e-7,0.00002101961,0.00003999011],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8476344,"threshold_uncertainty_score":0.2947109,"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."}}