{"id":"W4414539089","doi":"10.1109/icc52391.2025.11161524","title":"Genai Assistance for Deep Reinforcement Learning-Based VNF Placement and SFC Provisioning in 5G Cores","year":2025,"lang":"en","type":"article","venue":"","topic":"Semiconductor materials and interfaces","field":"Physics and Astronomy","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ciena (Canada); University of Ottawa","funders":"","keywords":"Reinforcement learning; Provisioning; Virtual network; Autoencoder; Virtualization; Flexibility (engineering); Throughput; Function (biology); Network Functions Virtualization; Dependability","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":[0.0005618208,0.0006950307,0.0005065058,0.0002441734,0.0003339655,0.0004967455,0.001006035,0.0007069747,0.003916892],"category_scores_gemma":[0.001457483,0.0002504354,0.0003429637,0.0002157411,0.0004752261,0.0005656117,0.000945815,0.0009757213,0.0005300117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006645876,"about_ca_system_score_gemma":0.001065981,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004784704,"about_ca_topic_score_gemma":0.008871753,"domain_scores_codex":[0.999777,0.00004552211,0.000008698908,0.0000631501,0.00005487109,0.00005079986],"domain_scores_gemma":[0.9996347,0.0001596491,0.00004191585,0.00003908947,0.00008933251,0.0000351257],"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":[0.0001221305,0.00007928427,0.001565628,0.00006144202,0.000031901,0.0001390108,0.00009024711,0.8419237,0.005067287,0.005864802,0.003157764,0.1418968],"study_design_scores_gemma":[0.000004820135,0.00001765754,0.00005277497,0.000002336054,0.000002692667,0.00001126926,0.000004526418,0.998235,0.0005782027,0.0006933459,0.0003952096,0.000002080839],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05213988,0.0004466945,0.9364094,0.0004414849,0.0001513427,0.00008452107,0.00008300945,0.002070253,0.008173354],"genre_scores_gemma":[0.869984,0.0001179713,0.1233658,0.0003217148,0.00004047383,0.0001098708,0.0001444814,0.0001068793,0.005808776],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004784704,"threshold_uncertainty_score":0.01310331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0098003985831968,"score_gpt":0.2670004774236625,"score_spread":0.2572000788404657,"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."}}