{"id":"W2014447686","doi":"10.1287/opre.1080.0601","title":"Technical Note—A Multiperiod Model of Inventory Competition","year":2009,"lang":"en","type":"article","venue":"Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Newsvendor model; Duopoly; Stockout; Substitution (logic); Inventory theory; Economics; Context (archaeology); Microeconomics; Inventory management; Mathematical economics; Computer science; Supply chain; Operations management; Business; Cournot competition","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":[0.0008557753,0.00008943069,0.0001216302,0.000508539,0.0003285656,0.0001967543,0.0002945973,0.00006009967,0.0004428102],"category_scores_gemma":[0.0001641982,0.00008533106,0.00005646123,0.0005679273,0.0001271513,0.0006689029,0.0001376048,0.0002152435,0.0002809905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007140727,"about_ca_system_score_gemma":0.00004633309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002459986,"about_ca_topic_score_gemma":0.0002678934,"domain_scores_codex":[0.9986908,0.0000276039,0.0002508056,0.0002182441,0.0005529635,0.0002595282],"domain_scores_gemma":[0.9992266,0.00001440455,0.00002151523,0.0003190133,0.0004019396,0.00001647863],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004168121,0.0006756578,0.0003546501,0.00008553296,0.000006238386,0.000003845227,0.0001309506,0.05763626,0.0681056,0.851031,0.0144992,0.007429346],"study_design_scores_gemma":[0.0003911756,0.00003417914,0.0007631318,0.0000379779,0.00000696468,2.560495e-7,0.0001867452,0.9754368,0.000598672,0.0029212,0.01949869,0.0001241863],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2785519,0.0001803716,0.08362491,0.01991261,0.0004331501,0.002777592,0.00001686566,0.0004311442,0.6140715],"genre_scores_gemma":[0.9947269,0.00001507004,0.002292748,0.0007474751,0.0002916907,0.00004592761,0.00005536792,0.00001077867,0.001814035],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9178005,"threshold_uncertainty_score":0.4848461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09884320516322087,"score_gpt":0.3497422375017635,"score_spread":0.2508990323385426,"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."}}