{"id":"W2231033513","doi":"10.1287/opre.2015.1443","title":"Technical Note—Sequential Multiproduct Price Competition in Supply Chain Networks","year":2016,"lang":"en","type":"article","venue":"Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Comparative statics; Competition (biology); Product (mathematics); Supply chain; Downstream (manufacturing); Microeconomics; Marginal cost; Economics; Upstream (networking); Industrial organization; Computer science; Business; Mathematics; Marketing; Operations management","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002107705,0.0001306822,0.0001370353,0.0007097484,0.0003737605,0.0003888816,0.0003787903,0.0000871345,0.001997024],"category_scores_gemma":[0.0004333562,0.00009900749,0.00004697362,0.001072873,0.0001807587,0.001027874,0.0003810935,0.0002829995,0.0009791529],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002163957,"about_ca_system_score_gemma":0.00004351475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009386861,"about_ca_topic_score_gemma":0.00257741,"domain_scores_codex":[0.9980771,0.00009528045,0.0003069027,0.0004404171,0.0005434011,0.0005368754],"domain_scores_gemma":[0.9991643,0.00007922374,0.00002215317,0.000414105,0.0002974751,0.00002277968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002138975,0.001245633,0.01229946,0.0001570168,0.00002230765,0.0000963748,0.0001342818,0.01829838,0.06847353,0.7842531,0.06000031,0.05480567],"study_design_scores_gemma":[0.003562778,0.00008668681,0.02661786,0.0004211172,0.00001610039,0.000005317703,0.000395213,0.365892,0.0009878235,0.001849286,0.5993837,0.0007822294],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2743796,0.0005103075,0.3051897,0.1429989,0.003589673,0.009506606,0.0000334792,0.001034237,0.2627575],"genre_scores_gemma":[0.9933188,0.00005805519,0.0006138752,0.0004429696,0.001598561,0.0002655777,0.00006327591,0.00002587228,0.003613045],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7824038,"threshold_uncertainty_score":0.9997987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05754119686171174,"score_gpt":0.3283737956289067,"score_spread":0.270832598767195,"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."}}