{"id":"W3177614009","doi":"10.32920/ryerson.14654346.v1","title":"Optimal inventory policy for the two-level supply chain with defective items","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Vendor; Supply chain; Business; Vendor-managed inventory; Order (exchange); Holding cost; Operations management; Work (physics); Industrial organization; Supply chain management; Marketing; Finance; Economics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001731748,0.001194957,0.001850853,0.001130018,0.0009056398,0.003471543,0.00192989,0.002137504,0.006969403],"category_scores_gemma":[0.002592714,0.001378965,0.001254789,0.00138095,0.001448144,0.002887225,0.001415677,0.001665279,0.0007007492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004513845,"about_ca_system_score_gemma":0.003084771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01693239,"about_ca_topic_score_gemma":0.01019562,"domain_scores_codex":[0.998831,0.0003647002,0.00004030779,0.0002615713,0.0001841226,0.0003183114],"domain_scores_gemma":[0.9986501,0.0006419061,0.0002520869,0.00006862135,0.0002248965,0.0001623029],"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":[0.00008835079,0.00004059714,0.0002722512,0.00006234516,0.00001464378,0.00007393046,0.00003038174,0.9915603,0.0005007251,0.004783431,0.0002505363,0.002322526],"study_design_scores_gemma":[0.00002506674,0.00006726939,0.0001535018,0.00001047235,0.00001234041,0.00001805074,0.00002525289,0.995053,0.0001717797,0.004171311,0.0002802034,0.000011748],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1753017,0.001053116,0.8057134,0.0008737852,0.00008624781,0.0003438154,0.0006367255,0.0004228899,0.01556835],"genre_scores_gemma":[0.9478884,0.0005925567,0.03894977,0.00008155488,0.00002710935,0.0002141598,0.0003034788,0.00007061851,0.01187222],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01693239,"threshold_uncertainty_score":0.03366768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04309384004535571,"score_gpt":0.2613715622066216,"score_spread":0.2182777221612658,"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."}}