{"id":"W4406499899","doi":"10.1109/cascon62161.2024.10838059","title":"Machine Learning-Based Control of Dual-Sourcing Inventory Systems","year":2024,"lang":"en","type":"article","venue":"","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Dual (grammatical number); Computer science; Control (management); Inventory control; Artificial intelligence; Operations research; Engineering","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":[0.002708869,0.001181744,0.001487304,0.0006083979,0.0005505466,0.002165799,0.00166803,0.001064086,0.001515693],"category_scores_gemma":[0.005847981,0.0006213143,0.0005812647,0.0006434271,0.001327782,0.001065541,0.001339695,0.001633289,0.0001959111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001567354,"about_ca_system_score_gemma":0.001840866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01240948,"about_ca_topic_score_gemma":0.00720305,"domain_scores_codex":[0.9987971,0.0003114252,0.00006205741,0.0002885911,0.0003287972,0.0002120903],"domain_scores_gemma":[0.9966066,0.001809818,0.0007197326,0.0001499148,0.0005519386,0.0001620462],"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":[0.0000338393,0.00002124309,0.0002223819,0.00001850958,0.000009011993,0.00003263836,0.00001594165,0.994001,0.0004016452,0.002074757,0.0001026489,0.003066384],"study_design_scores_gemma":[0.000003133217,0.0000116926,0.00004284515,0.000001256085,0.000001274346,0.000001973706,0.000001404165,0.999377,0.00007930511,0.0004416477,0.00003649801,0.000002117204],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1298225,0.0003634243,0.86068,0.0007215042,0.0001183369,0.0001398165,0.0002089703,0.0004739382,0.007471483],"genre_scores_gemma":[0.9881341,0.00008447452,0.01023624,0.00003252881,0.00001761011,0.00006096884,0.00004603891,0.00001190838,0.001376206],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01240948,"threshold_uncertainty_score":0.02467448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01484261192685949,"score_gpt":0.2074382560542809,"score_spread":0.1925956441274214,"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."}}