{"id":"W4413795156","doi":"10.3934/jimo.2025132","title":"Sustainable inventory models with reduction on environmental emission and ordering costs under the discount policy of prepayment","year":2025,"lang":"en","type":"article","venue":"Journal of Industrial and Management Optimization","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Prepayment of loan; Reduction (mathematics); Environmental policy; Computable general equilibrium; Economics; Environmental economics; Natural resource economics; Finance; Microeconomics; Mathematics","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":[0.00188918,0.001553407,0.001441103,0.00119787,0.0006692672,0.002294893,0.00218772,0.002007729,0.003761732],"category_scores_gemma":[0.002407531,0.001016783,0.001569704,0.001914432,0.001047381,0.002129558,0.001196716,0.001563329,0.0004350357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002956559,"about_ca_system_score_gemma":0.003053125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01693673,"about_ca_topic_score_gemma":0.01176183,"domain_scores_codex":[0.9991315,0.0003302885,0.00004090077,0.0001268985,0.0001941225,0.0001762854],"domain_scores_gemma":[0.9990231,0.0005540741,0.0001637217,0.00004425686,0.0001540522,0.00006071273],"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":[0.00001477422,0.00001147021,0.00009728588,0.00001759126,0.000005975633,0.00002460624,0.00001113354,0.9919571,0.00009633594,0.006510616,0.00008673026,0.001166403],"study_design_scores_gemma":[0.000005947673,0.00001719548,0.00005405777,0.000005520216,0.000006082584,0.000007263166,0.00001160563,0.9954645,0.00005312475,0.004114711,0.0002555902,0.000004431749],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09547582,0.001911408,0.8683632,0.001010351,0.0001391165,0.0002793346,0.0009665653,0.0003246029,0.03152969],"genre_scores_gemma":[0.9168232,0.00191285,0.06226125,0.0001092461,0.00005391277,0.0004176132,0.0004987512,0.00007320405,0.01784996],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01693673,"threshold_uncertainty_score":0.03367627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01722340894944482,"score_gpt":0.2176422189966326,"score_spread":0.2004188100471877,"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."}}