{"id":"W4412210974","doi":"","title":"Deep Reinforcement Learning for Revenue Management under Uncertainty in Master Stowage Planning on Container Vessels","year":2025,"lang":"en","type":"article","venue":"IT University Of Copenhagen (IT University of Copenhagen)","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Stowage; Container (type theory); Reinforcement learning; Revenue; Reinforcement; Operations research; Computer science; Business; Engineering; Artificial intelligence; Finance; Mechanical engineering; Structural engineering","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000333433,0.0002462433,0.0004835131,0.0003140208,0.0002065767,0.00002028214,0.0005060734,0.000152563,0.009976569],"category_scores_gemma":[0.00001772895,0.0003393918,0.0001473632,0.0003061636,0.0001237091,0.0002021667,0.0001933537,0.0002496825,0.0002607657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002888441,"about_ca_system_score_gemma":0.00006740495,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002959548,"about_ca_topic_score_gemma":0.0004034991,"domain_scores_codex":[0.998732,0.00007035424,0.000283552,0.0003243528,0.0002265793,0.0003631796],"domain_scores_gemma":[0.999141,0.000170621,0.0001599922,0.0003200913,0.0001195502,0.00008870268],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004328444,0.00005863897,0.00003124612,0.0004552923,0.0002563227,0.0001596871,0.001525979,0.8179261,0.0001032826,0.00158294,0.175404,0.002063693],"study_design_scores_gemma":[0.004446602,0.0002707142,0.003422289,0.0009324009,0.0003187469,0.000001325757,0.02039196,0.09032285,0.0003009263,0.00005396745,0.8790053,0.000532893],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02719017,0.0004334983,0.435331,0.0004440107,0.0002610035,0.001341845,0.00004202346,0.0000967427,0.5348597],"genre_scores_gemma":[0.7985821,0.0001076778,0.0008749006,0.000114895,0.000008638604,3.151133e-7,0.00006212696,0.00001584885,0.2002335],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7713919,"threshold_uncertainty_score":0.9999058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01855876090244227,"score_gpt":0.2175407779483694,"score_spread":0.1989820170459272,"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."}}