{"id":"W3120714101","doi":"10.3390/logistics5010003","title":"A Model for Demand Planning in Supply Chains with Congestion Effects","year":2021,"lang":"en","type":"article","venue":"Logistics","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Aggregate planning; Computer science; Plan (archaeology); Demand management; Supply and demand; Supply chain; Operations research; Clearing; Production planning; Order (exchange); Workstation; Demand forecasting; Production (economics); Economics; Business; Engineering; Microeconomics","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":[0.0009300524,0.0008426098,0.0007464261,0.0004803457,0.0008538846,0.002027804,0.001585629,0.001715236,0.007363135],"category_scores_gemma":[0.0022369,0.0007365956,0.0007662326,0.001138931,0.001482529,0.00204805,0.001219039,0.001963646,0.0006161022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002942276,"about_ca_system_score_gemma":0.002666788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02431223,"about_ca_topic_score_gemma":0.01564143,"domain_scores_codex":[0.999437,0.0001886145,0.0000234608,0.0001238493,0.0001242676,0.000102786],"domain_scores_gemma":[0.9992359,0.0004421576,0.0000857093,0.00003692591,0.000121593,0.00007768159],"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":[0.00001541505,0.00001252816,0.00008942674,0.00001758185,0.000003942372,0.00004452705,0.00003604796,0.9689887,0.0002394702,0.02875466,0.0003084424,0.001489288],"study_design_scores_gemma":[0.000009781702,0.00000858415,0.00003315308,0.000002960938,0.000002988376,0.000008417218,0.00001166632,0.9908705,0.00006545114,0.008256827,0.0007253135,0.000004369799],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02833899,0.0001794987,0.9563118,0.0007707478,0.00004208527,0.0001010479,0.0003983518,0.0002796097,0.01357803],"genre_scores_gemma":[0.8133141,0.000585303,0.1514191,0.0002201903,0.0001026198,0.0004896344,0.000639116,0.0001379606,0.03309193],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02431223,"threshold_uncertainty_score":0.04834145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04790409707065878,"score_gpt":0.2539294956017751,"score_spread":0.2060253985311163,"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."}}