{"id":"W2048612773","doi":"10.1080/07408170304351","title":"Managing Demand to Optimize Production Costs","year":2003,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"University of Louisville","keywords":"Production (economics); Economics; Product (mathematics); Time horizon; Demand forecasting; Microeconomics; Derived demand; Aggregate demand; Demand management; Control (management); Demand patterns; Monotone polygon; Industrial organization; Econometrics; Demand curve; Operations management; Mathematics; Monetary economics","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":[0.0006884456,0.0006062927,0.000718358,0.0004715102,0.0003793507,0.001701679,0.0006451587,0.0006143873,0.001553842],"category_scores_gemma":[0.002334089,0.0003528419,0.0002577674,0.0009316924,0.0003176665,0.001555357,0.0004858975,0.0004811441,0.0003024387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001420899,"about_ca_system_score_gemma":0.00153146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002456526,"about_ca_topic_score_gemma":0.002461237,"domain_scores_codex":[0.999375,0.0001601291,0.0000317443,0.0001121059,0.0001772674,0.000143811],"domain_scores_gemma":[0.9994733,0.0002323541,0.0001086619,0.00005000829,0.00009532101,0.00004045788],"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":[0.00008932625,0.00008610877,0.002563799,0.0001024697,0.00003210324,0.00008641975,0.0001207384,0.9280121,0.01038919,0.01765622,0.001065068,0.03979635],"study_design_scores_gemma":[0.00001687663,0.00009270815,0.001265982,0.00001065155,0.00001785274,0.0000668575,0.0001458788,0.9790562,0.003056358,0.01460991,0.00164646,0.00001432208],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3831419,0.0006590016,0.5975179,0.000927442,0.00003434222,0.0001745892,0.0001844656,0.0003868632,0.01697347],"genre_scores_gemma":[0.9798422,0.0001956865,0.0186623,0.00003677142,0.00001082277,0.00004885593,0.00005369803,0.00003909723,0.001110477],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002456526,"threshold_uncertainty_score":0.0103094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01955066143324833,"score_gpt":0.2227023180082883,"score_spread":0.2031516565750399,"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."}}