{"id":"W2058302761","doi":"10.1007/s10479-006-7371-4","title":"On the interaction between retailers inventory policies and manufacturer trade deals in response to supply-uncertainty occurrences","year":2006,"lang":"en","type":"article","venue":"Annals of Operations Research","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Fredericton; University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Theory of computation; Interval (graph theory); Point (geometry); Duration (music); Random variable; Operations research; Computer science; Variable (mathematics); Probability distribution; Supply chain; Distribution (mathematics); Mathematical optimization; Econometrics; Industrial organization; Microeconomics; Business; Economics; Mathematics; Statistics; Marketing; Algorithm","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004302153,0.0003176566,0.000840754,0.0006960956,0.0006085818,0.00342485,0.0008962892,0.001896894,0.008086334],"category_scores_gemma":[0.02867017,0.0006047301,0.0006684564,0.0009564229,0.001423483,0.002227423,0.00111017,0.002369138,0.0004070086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001372012,"about_ca_system_score_gemma":0.0008838195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008040852,"about_ca_topic_score_gemma":0.007752745,"domain_scores_codex":[0.9989902,0.0005135842,0.00004713299,0.0001164326,0.00009574732,0.0002368339],"domain_scores_gemma":[0.9271082,0.06822848,0.002326683,0.0005008639,0.0009248406,0.0009109757],"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":[0.006280549,0.001270521,0.1442678,0.0003365742,0.0007195334,0.002177864,0.003045897,0.6793423,0.01075605,0.1052992,0.007599055,0.03890469],"study_design_scores_gemma":[0.0001158348,0.000375848,0.07803484,0.00004331708,0.0002326065,0.0001857218,0.003410248,0.84236,0.001155167,0.07251072,0.001456734,0.0001189671],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9743502,0.0004110096,0.008768698,0.003243486,0.00006648597,0.00004335287,0.0002508118,0.00004721297,0.01281889],"genre_scores_gemma":[0.9983405,0.0001367267,0.0003310619,0.00006183662,0.00002159952,0.000008041939,0.00004209971,0.0000108531,0.00104731],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008086334,"threshold_uncertainty_score":0.02705145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1807015972807431,"score_gpt":0.3951230409874519,"score_spread":0.2144214437067088,"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."}}