{"id":"W4408324524","doi":"10.1109/globecom52923.2024.10901065","title":"Semantic Routing for Enhanced Performance of LLM-Assisted Intent-Based 5G Core Network Management and Orchestration","year":2024,"lang":"en","type":"article","venue":"","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Orchestration; Computer science; Routing (electronic design automation); Computer network; Core (optical fiber); Network Functions Virtualization; Distributed computing; Cloud computing; Telecommunications; Operating system","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":[0.001299606,0.0006056738,0.0005323234,0.0006378772,0.0005252318,0.0009877171,0.0006764943,0.0004411899,0.001790377],"category_scores_gemma":[0.004815761,0.0001678945,0.0001880854,0.000556078,0.0004206606,0.001580071,0.001204639,0.0008661588,0.0006747902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006706067,"about_ca_system_score_gemma":0.0007702216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00269616,"about_ca_topic_score_gemma":0.004327882,"domain_scores_codex":[0.9993314,0.0002031873,0.00004753974,0.0001150475,0.0002065826,0.00009637807],"domain_scores_gemma":[0.9989519,0.0004255519,0.00005710863,0.000321802,0.0001927152,0.00005082667],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001986903,0.0006072848,0.008613259,0.0003027352,0.00008794832,0.000469149,0.0004967538,0.2323762,0.07231645,0.01223111,0.01849521,0.6520171],"study_design_scores_gemma":[0.00003915657,0.0001683751,0.001035971,0.00001368135,0.00001596092,0.0001078164,0.0001020576,0.9567026,0.03394236,0.004647225,0.00319922,0.00002560087],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5362895,0.001024311,0.4138631,0.0009089395,0.0003127886,0.0002113261,0.001198898,0.03717555,0.009015457],"genre_scores_gemma":[0.9248699,0.00009763039,0.07289199,0.0001106583,0.00002017516,0.00003006136,0.0009351468,0.0001561178,0.0008883589],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00269616,"threshold_uncertainty_score":0.006873071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0289364951687631,"score_gpt":0.2536792257205959,"score_spread":0.2247427305518328,"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."}}