{"id":"W4394698768","doi":"10.1109/tnsm.2024.3387275","title":"VNF Placement and Dynamic NUMA Node Selection Through Core Consolidation at the Edge and Cloud","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Network and Service Management","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Cloud computing; Computer network; Enhanced Data Rates for GSM Evolution; Distributed computing; Selection (genetic algorithm); Consolidation (business); Node (physics); Operating system; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002244257,0.0001993637,0.0001344946,0.00005617597,0.0006644998,0.000330578,0.000148952,0.00006387832,0.00002473472],"category_scores_gemma":[2.810285e-7,0.0001559717,0.00003267156,0.0005386223,0.00004561154,0.0002257299,0.00002731612,0.0001805158,0.00001839551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007098748,"about_ca_system_score_gemma":0.00001162453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004310204,"about_ca_topic_score_gemma":0.0005026218,"domain_scores_codex":[0.998796,0.00005214537,0.0001932167,0.0004985645,0.0001826796,0.000277376],"domain_scores_gemma":[0.9994612,0.000155487,0.00003846087,0.0002573509,0.00002697256,0.00006047925],"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":[0.0002302705,0.0001849743,0.000155037,0.0009033328,0.0007764749,0.00004149557,0.005654521,0.456383,0.00004981115,0.02715014,0.02065544,0.4878155],"study_design_scores_gemma":[0.000656469,0.0001587497,0.0007440263,0.0002296439,0.0001821028,0.00006304371,0.0002458528,0.9404829,0.00003659105,0.002271867,0.05459844,0.0003302871],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02544484,0.001571728,0.9656549,0.004066397,0.001656918,0.0005001119,0.000005790771,0.0002627115,0.000836659],"genre_scores_gemma":[0.9799317,0.00871039,0.005606097,0.004137775,0.0002345017,0.0001515979,0.00001095968,0.00003054026,0.001186498],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9600487,"threshold_uncertainty_score":0.6360343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01529738570642861,"score_gpt":0.2417130690816116,"score_spread":0.226415683375183,"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."}}