{"id":"W2162598493","doi":"10.1287/trsc.1030.0022","title":"Coffee, Tea, or …?: A Markov Decision Process Model for Airline Meal Provisioning","year":2004,"lang":"en","type":"article","venue":"Transportation Science","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Mitacs","keywords":"Markov decision process; Provisioning; Operations research; Markov process; Process (computing); Computer science; Decision process; Liberian dollar; Upload; Service (business); Decision model; Business; Engineering; Marketing; Mathematics; Telecommunications; Process management; Statistics; Finance","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007303979,0.0001524359,0.0001420613,0.0003515706,0.0004595126,0.0002509632,0.0004314295,0.00003282621,0.00009867804],"category_scores_gemma":[0.0001114348,0.0001196914,0.00005798638,0.001081902,0.0001492262,0.00233957,0.00001333077,0.00006001562,0.00003079055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005637629,"about_ca_system_score_gemma":0.0001696175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007428034,"about_ca_topic_score_gemma":0.0004584741,"domain_scores_codex":[0.998156,0.00000121269,0.00034891,0.0004644452,0.0006904778,0.000338982],"domain_scores_gemma":[0.9992358,0.0000241136,0.0001609231,0.0001874879,0.000363004,0.00002867411],"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":[0.00175613,0.0007343605,0.008316513,0.001265892,0.00002616124,0.00002826421,0.004100045,0.7790788,0.002816482,0.1211621,0.00251519,0.07820005],"study_design_scores_gemma":[0.003596276,0.000063094,0.01277902,0.0002557266,0.00007150038,5.710771e-7,0.001374306,0.9457665,0.0006620458,0.02960528,0.005307579,0.0005181198],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5079147,0.00001136001,0.4880553,0.000770662,0.0003063094,0.0009738929,0.000007091944,0.0001665287,0.001794125],"genre_scores_gemma":[0.9872036,0.000002881417,0.01055771,0.001492163,0.0001507479,0.0001173109,0.0000357643,0.0000179643,0.000421869],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4792889,"threshold_uncertainty_score":0.4880875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03722817832996832,"score_gpt":0.3009554420369594,"score_spread":0.2637272637069911,"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."}}