{"id":"W4414567802","doi":"10.1016/j.ifacol.2025.09.059","title":"Inventory Management for Perishable Two-Echelon Supply Chains","year":2025,"lang":"en","type":"article","venue":"IFAC-PapersOnLine","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Dalhousie University","funders":"","keywords":"Supply chain; Economic order quantity; Inventory management; Supply chain management; Product (mathematics); Supply chain risk management; Order (exchange); Inventory theory","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":[0.00007864244,0.0001693478,0.0001589447,0.0001191052,0.0000972285,0.0000281595,0.0001336993,0.00006385394,0.00003690323],"category_scores_gemma":[0.00002327042,0.0001790773,0.00006250611,0.0001232011,0.00002432683,0.00007446246,0.00003334531,0.0001057158,0.00001150009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001201447,"about_ca_system_score_gemma":0.000009907316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008716695,"about_ca_topic_score_gemma":0.00002427753,"domain_scores_codex":[0.9992501,0.000006878889,0.0001755017,0.0002092728,0.00008218527,0.0002760864],"domain_scores_gemma":[0.9996516,0.00003350317,0.00002220841,0.0002145105,0.00003024655,0.00004790469],"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":[0.00002475179,0.00004513855,0.00007690543,0.0003938037,0.00009808464,0.000005073117,0.0001439109,0.9745975,0.0004385587,0.007493762,0.000396398,0.01628613],"study_design_scores_gemma":[0.001977325,0.00005624169,0.000421631,0.0001469874,0.0001030322,0.00000161532,0.0003894802,0.9443296,0.005051958,0.002086587,0.04496448,0.0004710309],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006780853,0.0007478561,0.964686,0.0004361241,0.000999323,0.0006492619,0.00008349551,0.0007854194,0.02483169],"genre_scores_gemma":[0.192108,0.0004742399,0.7863054,0.0003823849,0.0002197617,0.0001833585,0.0003372785,0.00006056555,0.01992903],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1853272,"threshold_uncertainty_score":0.730256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007822622411039173,"score_gpt":0.2485136881660169,"score_spread":0.2406910657549777,"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."}}