{"id":"W4415818158","doi":"10.1287/mnsc.2023.03157","title":"Deep Neural Newsvendor","year":2025,"lang":"en","type":"article","venue":"Management Science","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Quantile; Newsvendor model; Artificial neural network; Range (aeronautics); Smoothness; Function (biology); Extant taxon; Feature (linguistics); Dimension (graph theory)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002591694,0.0009300897,0.00180255,0.0007490859,0.0005477019,0.002134618,0.001940891,0.002986336,0.005555349],"category_scores_gemma":[0.009919167,0.0008077895,0.0008094577,0.0009844684,0.001387874,0.003239389,0.001323796,0.00263454,0.0003857362],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002428421,"about_ca_system_score_gemma":0.001047868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01033557,"about_ca_topic_score_gemma":0.006874715,"domain_scores_codex":[0.9993123,0.0002186244,0.00004488917,0.0002230793,0.00008195265,0.000119128],"domain_scores_gemma":[0.9957633,0.003117518,0.0004407231,0.0001414161,0.0003604165,0.0001765752],"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":[0.0001143851,0.00004425908,0.001413339,0.00008469164,0.00005607372,0.0001953512,0.00005150573,0.9443426,0.0002186991,0.03751223,0.002288438,0.01367857],"study_design_scores_gemma":[0.00000672256,0.000008034541,0.0001017599,0.000005895144,0.000005969961,0.00001093862,0.000009068409,0.9872224,0.00006980606,0.01229169,0.0002627368,0.000005087406],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1883812,0.003279037,0.7827261,0.006162512,0.00046065,0.00009508534,0.001145541,0.0006477585,0.01710211],"genre_scores_gemma":[0.9639447,0.0007707493,0.02522846,0.000373913,0.0001585428,0.00009350447,0.0005150331,0.00006716337,0.008847964],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01033557,"threshold_uncertainty_score":0.02055079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0128674953420305,"score_gpt":0.2346773439220108,"score_spread":0.2218098485799803,"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."}}