{"id":"W4297998800","doi":"10.1287/mnsc.2022.4547","title":"Analytical Solution to a Partially Observable Machine Maintenance Problem with Obvious Failures","year":2022,"lang":"en","type":"article","venue":"Management Science","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Unobservable; Observable; Mathematical optimization; Partially observable Markov decision process; Computer science; Markov decision process; Preventive maintenance; Markov chain; Markov process; Mathematics; Markov model; Reliability engineering; Econometrics; Engineering; Machine learning; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006048359,0.0001073587,0.00009781891,0.0001436427,0.0003621953,0.00009395862,0.0004103104,0.00000923932,0.00008226637],"category_scores_gemma":[0.00001397949,0.00009363717,0.00002023114,0.00131627,0.0001106925,0.0002663629,0.000261767,0.00009970198,0.0000218536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000290098,"about_ca_system_score_gemma":0.00001928259,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005093514,"about_ca_topic_score_gemma":0.00006913798,"domain_scores_codex":[0.9985676,0.00001484064,0.0001512301,0.0003363522,0.0004931251,0.0004368639],"domain_scores_gemma":[0.9995418,0.000006825643,0.00002119591,0.0002972292,0.000039378,0.00009362451],"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":[0.00002069812,0.00002991021,0.0004843878,0.00003451752,0.000007818347,0.00001140529,0.0001160194,0.9796892,0.0001580774,0.01444644,0.002740831,0.00226068],"study_design_scores_gemma":[0.0002449584,0.0001511176,0.002586375,0.00002118471,0.00001554433,0.000005328468,0.0001836959,0.9532608,0.0001005548,0.0005169096,0.04271657,0.0001969897],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04434909,0.00004857577,0.8961064,0.005250927,0.0004067247,0.001689778,0.00001284305,0.0006939918,0.05144173],"genre_scores_gemma":[0.9640421,0.00001335049,0.03371736,0.0002945908,0.000009959931,0.0002201475,0.000004749139,0.00001296554,0.001684724],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9196931,"threshold_uncertainty_score":0.3818413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007291141728701682,"score_gpt":0.197415681817127,"score_spread":0.1901245400884253,"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."}}