{"id":"W4411600806","doi":"10.1109/tnsm.2025.3582223","title":"FR-SFCO: Energy-Aware Offloading on Data Plane for Delay-Sensitive SFC","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Network and Service Management","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Major Research Plan; National Natural Science Foundation of China","keywords":"Computer science; Forwarding plane; Energy consumption; Computer network; Network packet; Electrical 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002345668,0.0001818589,0.0001710477,0.0001682637,0.0004500645,0.0001487277,0.0006495817,0.00006436358,0.000002541133],"category_scores_gemma":[5.011122e-7,0.0001821612,0.00003836827,0.0005269853,0.00001291968,0.0001535409,0.00003492534,0.0001096411,0.00000411325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003449516,"about_ca_system_score_gemma":0.00001746612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005113008,"about_ca_topic_score_gemma":0.0001157515,"domain_scores_codex":[0.9987473,0.00005623098,0.0002105277,0.0005725938,0.0001402319,0.0002730455],"domain_scores_gemma":[0.9989049,0.0001692092,0.00005611273,0.0007503668,0.00006384584,0.00005551021],"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":[0.0001041278,0.0001476777,0.000001817968,0.0001151902,0.0002525282,0.00001372053,0.0001465382,0.6680531,0.000003191157,0.02825616,0.01916694,0.283739],"study_design_scores_gemma":[0.0004079863,0.00009059435,0.0000151117,0.0001890453,0.00005389615,0.000002023686,0.00003482786,0.9631724,0.0002740105,0.001080362,0.03448877,0.0001909934],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0000607166,0.00003964229,0.9914562,0.002015145,0.0005670415,0.0002932277,0.00002065142,0.0003665148,0.005180873],"genre_scores_gemma":[0.7967901,0.0009903326,0.1828679,0.01704633,0.0001498738,0.0001379982,0.00008767548,0.00002768186,0.001902049],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8085883,"threshold_uncertainty_score":0.7428318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0220412443046076,"score_gpt":0.2585684639979712,"score_spread":0.2365272196933636,"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."}}