{"id":"W3029114129","doi":"10.1007/s10479-020-03642-4","title":"The distributionally robust optimization model for a remanufacturing system under cap-and-trade policy: a newsvendor approach","year":2020,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":63,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"Taishan Scholar Foundation of Shandong Province; National Natural Science Foundation of China","keywords":"Newsvendor model; Remanufacturing; Theory of computation; Robust optimization; Computer science; Mathematical optimization; Operations research; Business; Mathematics; Supply chain; Algorithm; Manufacturing engineering; 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":[],"consensus_categories":[],"category_scores_codex":[0.001383136,0.0001249076,0.0001552225,0.0002518339,0.001144884,0.0007074281,0.0003564857,0.00004960952,0.000005849247],"category_scores_gemma":[0.0007357139,0.00009834362,0.00006855428,0.0007253635,0.0001277189,0.0006262959,0.0003159359,0.0001549235,0.000004059075],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006342533,"about_ca_system_score_gemma":0.0001592249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004490515,"about_ca_topic_score_gemma":0.00003970711,"domain_scores_codex":[0.9983717,0.00005011499,0.0003179887,0.0003048619,0.000518196,0.0004371205],"domain_scores_gemma":[0.9988301,0.0001338297,0.00005370325,0.0002412267,0.0007062366,0.00003493788],"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":[0.00004068292,0.00002469035,0.00001174982,0.000332202,0.00003407374,4.813621e-7,0.00009476194,0.740553,0.00001079631,0.2521252,0.006555058,0.0002172331],"study_design_scores_gemma":[0.0002816373,0.0000137666,0.00005887838,0.00001970103,0.00001282876,4.156832e-7,0.003859743,0.9904422,0.00003450526,0.0007275867,0.004451386,0.0000973666],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002183971,0.0001789967,0.8452778,0.1479245,0.00002155882,0.001743512,0.00003246156,0.00006717535,0.00257009],"genre_scores_gemma":[0.9917777,0.00005709004,0.004917963,0.001537255,0.0005705901,0.0004312281,0.000195561,0.00003020572,0.0004824157],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9895937,"threshold_uncertainty_score":0.880564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.211452882669301,"score_gpt":0.3585557259986584,"score_spread":0.1471028433293574,"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."}}