{"id":"W4399258900","doi":"10.1016/j.cor.2024.106711","title":"Approximate linear programming for a queueing control problem","year":2024,"lang":"en","type":"article","venue":"Computers & Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Queueing theory; Computer science; Mathematical optimization; Linear programming; Control (management); Mathematics; Computer network; Artificial intelligence","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":[0.003226401,0.001354618,0.002191227,0.001073591,0.0009297936,0.00313221,0.002295012,0.00345178,0.006167235],"category_scores_gemma":[0.01898453,0.001149006,0.001043089,0.001364981,0.001820232,0.002765486,0.002147969,0.002847067,0.00036656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003599563,"about_ca_system_score_gemma":0.003227915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02053377,"about_ca_topic_score_gemma":0.008480154,"domain_scores_codex":[0.9982871,0.0007775211,0.00006165783,0.0002610206,0.0003589842,0.0002535731],"domain_scores_gemma":[0.9898366,0.008900108,0.0002740611,0.0001896415,0.000546435,0.0002530704],"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":[0.0001344952,0.00008920774,0.0002213004,0.0001025279,0.00002777578,0.00004421346,0.00005661015,0.9460647,0.0003859595,0.04254381,0.00134961,0.008979803],"study_design_scores_gemma":[0.00001046978,0.00001078897,0.0000227887,0.000003338565,0.000003740575,0.000003354315,0.000007094681,0.9896152,0.00004003198,0.01016589,0.0001146834,0.000002667159],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02709832,0.0007816632,0.9632396,0.001653182,0.000143956,0.0001006655,0.0001597979,0.0001728774,0.006649823],"genre_scores_gemma":[0.7948644,0.001101266,0.182133,0.0005287013,0.0004538168,0.0005334703,0.000519398,0.0002345234,0.01963149],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02053377,"threshold_uncertainty_score":0.04082853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07480078927415756,"score_gpt":0.3496103170099966,"score_spread":0.274809527735839,"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."}}