{"id":"W2154692792","doi":"10.1287/opre.1100.0810","title":"Dynamic Supplier Contracts Under Asymmetric Inventory Information","year":2010,"lang":"en","type":"article","venue":"Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Purchasing; Supply chain; Adverse selection; Business; Order (exchange); Economic order quantity; Downstream (manufacturing); Lead time; Value (mathematics); Microeconomics; Information asymmetry; Operations research; Computer science; Economics; Marketing; Actuarial science; Finance","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":[0.009042578,0.001104644,0.002094389,0.001028762,0.001467162,0.003060193,0.002661015,0.003568825,0.00555202],"category_scores_gemma":[0.02045535,0.001475841,0.001077706,0.001751236,0.002608779,0.005864782,0.002491374,0.002748286,0.0004978053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003303056,"about_ca_system_score_gemma":0.003037473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006689023,"about_ca_topic_score_gemma":0.0035578,"domain_scores_codex":[0.9937496,0.002815006,0.0002982547,0.0008456856,0.001102405,0.001189021],"domain_scores_gemma":[0.9733217,0.0162649,0.006153198,0.001474398,0.001589331,0.001196455],"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":[0.0003534479,0.0001484496,0.002561526,0.00008471173,0.00007114271,0.0009009931,0.0002583495,0.855953,0.001176639,0.1308009,0.0008996674,0.006791328],"study_design_scores_gemma":[0.0001062474,0.0001183124,0.0007554233,0.00002144424,0.00002992293,0.0001582079,0.0001469124,0.9164378,0.0003580461,0.08096929,0.0008521865,0.00004623404],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.493995,0.0009668875,0.4775114,0.003009062,0.0001123412,0.0002470573,0.0005986132,0.0002313346,0.02332824],"genre_scores_gemma":[0.9812437,0.0004432049,0.011588,0.0001573724,0.00006471555,0.00009671276,0.0001112648,0.00002500745,0.006269961],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009042578,"threshold_uncertainty_score":0.0478223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03740602588520761,"score_gpt":0.315609858055762,"score_spread":0.2782038321705543,"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."}}