{"id":"W7130846274","doi":"10.32628/cseit241061243","title":"Applied Performance Optimization Frameworks for Managing High Traffic and Peak Demand in Mobile Packet Core Networks","year":2024,"lang":"","type":"article","venue":"International Journal of Scientific Research in Computer Science Engineering and Information Technology","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bell (Canada); Microsoft (Canada)","funders":"","keywords":"Network traffic control; Network packet; Packet loss; Key (lock); Traffic generation model; Quality of service; Core network; Processing delay; Network performance; Resource allocation","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":[0.002646445,0.001380182,0.0007259591,0.0007755772,0.0004802567,0.001554601,0.001358259,0.0005693199,0.0006168254],"category_scores_gemma":[0.002758808,0.0003625844,0.0005094312,0.0006553849,0.0007688727,0.001001443,0.001213657,0.001015052,0.0001097061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002159285,"about_ca_system_score_gemma":0.002549564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007857803,"about_ca_topic_score_gemma":0.004648403,"domain_scores_codex":[0.9988649,0.0003995384,0.00004427399,0.0001049072,0.0004164704,0.0001699155],"domain_scores_gemma":[0.9992229,0.0003537994,0.0001141827,0.0000554254,0.00021383,0.0000398444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000008806688,0.00001518247,0.0001744003,0.00001161934,0.000009482155,0.000009903552,0.00001429911,0.986288,0.0005075841,0.007235158,0.0001383488,0.005587331],"study_design_scores_gemma":[7.689396e-7,0.000006110934,0.00003008654,0.000001729606,0.000002009887,0.000001758513,0.000003630491,0.9985643,0.0001533058,0.00110254,0.0001322281,0.000001559404],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02015066,0.0003779966,0.9758717,0.0001668298,0.00002428099,0.00006361992,0.00002966249,0.0002963095,0.003018916],"genre_scores_gemma":[0.8531726,0.0006979689,0.1441925,0.00007325098,0.00005598807,0.0002090013,0.0000972163,0.0001270766,0.001374477],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007857803,"threshold_uncertainty_score":0.01566678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01531224680550924,"score_gpt":0.281441088820384,"score_spread":0.2661288420148748,"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."}}