{"id":"W4312467276","doi":"10.2139/ssrn.4295869","title":"Optimal Robust Sourcing with Volume Flexibility: Anticipatory Ordering Using the Shifting Operator","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Operator (biology); Flexibility (engineering); Volume (thermodynamics); Econometrics; Computer science; Mathematics; Mathematical optimization; Statistics; Biology; Physics","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":[0.002971914,0.001165003,0.002065734,0.0005324328,0.000546838,0.002203807,0.001620174,0.001540873,0.00326783],"category_scores_gemma":[0.008051337,0.001117644,0.0008815213,0.0008749748,0.001638193,0.003385952,0.001585966,0.001863972,0.0002320388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001069512,"about_ca_system_score_gemma":0.002497465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004763921,"about_ca_topic_score_gemma":0.003099161,"domain_scores_codex":[0.9989101,0.0003949488,0.00006432217,0.0002489006,0.0001906388,0.0001911327],"domain_scores_gemma":[0.9963264,0.002505206,0.0004546454,0.0002361206,0.0002723278,0.0002053099],"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":[0.0003506889,0.00009194623,0.0004307554,0.00008942708,0.00005655597,0.0001476549,0.00006808355,0.9432421,0.003027888,0.03578687,0.0007810245,0.01592695],"study_design_scores_gemma":[0.00001973848,0.00006442071,0.00008320781,0.000006434239,0.00001435585,0.00001400381,0.00001641057,0.9815084,0.0003715093,0.01771859,0.0001657141,0.00001721503],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08532564,0.000420006,0.9075631,0.0008660142,0.0001581267,0.00006608879,0.00009122888,0.0001658233,0.005343977],"genre_scores_gemma":[0.9623672,0.0002908736,0.03417091,0.00007265006,0.00009363302,0.00003248002,0.00004451754,0.00004308136,0.002884722],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004763921,"threshold_uncertainty_score":0.01571721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02961481448058774,"score_gpt":0.2306161533967333,"score_spread":0.2010013389161456,"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."}}