{"id":"W2971262151","doi":"10.1049/iet-com.2019.0187","title":"Energy‐efficient BBU pool virtualisation for C‐RAN with quality of service guarantees","year":2019,"lang":"en","type":"article","venue":"IET Communications","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"National Telecommunication Regulatory Authority","keywords":"C-RAN; Virtualization; Computer science; Quality of service; Ran; Service (business); Computer network; Energy (signal processing); Business; Radio access network; Operating system; Mathematics; Cloud computing; Marketing; Base station","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":[0.0004057247,0.0001015853,0.0001824664,0.00006106614,0.0001541704,0.00004874956,0.001711136,0.00005030045,0.000008200348],"category_scores_gemma":[0.00003201209,0.00008747391,0.00006054707,0.0004988731,0.0000528118,0.0001607971,0.0003036948,0.00007720542,0.00001246954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002408735,"about_ca_system_score_gemma":0.00007426004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005320616,"about_ca_topic_score_gemma":0.0005382859,"domain_scores_codex":[0.9989918,0.0001436622,0.0003106391,0.0002033345,0.0001962443,0.0001542672],"domain_scores_gemma":[0.9958994,0.0009292645,0.0002163271,0.002582277,0.0003352087,0.00003746265],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005505649,0.0004314302,0.002148222,0.00006393955,0.000066359,7.318615e-8,0.003394258,0.01919687,0.001381279,0.959032,0.0006324211,0.01359811],"study_design_scores_gemma":[0.001740592,0.0002999772,0.01486536,0.0001550155,0.00003133116,0.000004312093,0.0005330225,0.9548015,0.001357809,0.007367703,0.01839266,0.0004507152],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09082156,0.0003970775,0.9008563,0.005903319,0.0001207488,0.0003807728,0.00003115802,0.0001659291,0.00132311],"genre_scores_gemma":[0.9536888,0.00003427944,0.04521978,0.0008208028,0.00001418717,0.00007741198,0.00005059674,0.000009953938,0.00008421867],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9516643,"threshold_uncertainty_score":0.3567083,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0429144062498023,"score_gpt":0.2906401434294957,"score_spread":0.2477257371796934,"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."}}