{"id":"W3144080483","doi":"10.1109/noms54207.2022.9789791","title":"Resource Management in Softwarized Networks","year":2022,"lang":"en","type":"article","venue":"NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Network management; Scalability; Network architecture; Computer network; Software-defined networking; Resource management (computing); Distributed computing; Resource allocation; Network monitoring; Survivability","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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.001485852,0.0004932304,0.0004775573,0.0004691334,0.001851265,0.000619264,0.001460961,0.0001001511,0.0002182637],"category_scores_gemma":[0.000003348585,0.0005437008,0.000154755,0.002582462,0.00007954601,0.0004936985,0.002537742,0.0006722598,0.0000217985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002705222,"about_ca_system_score_gemma":0.00003239626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000700169,"about_ca_topic_score_gemma":0.0001029097,"domain_scores_codex":[0.9955173,0.0004362428,0.0008002454,0.001402969,0.0007297097,0.001113595],"domain_scores_gemma":[0.9981341,0.0001373401,0.000141525,0.001335065,0.00003610441,0.0002158399],"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":[0.00004858048,0.0002306355,0.0007139069,0.00003179654,0.00018866,0.0002129669,0.000294706,0.8076045,0.000007297891,0.1007033,0.07389768,0.01606596],"study_design_scores_gemma":[0.002091243,0.0001966952,0.001496339,0.00004987382,0.0001099479,0.00003216146,0.0003599203,0.621982,0.000001845035,0.001153239,0.371706,0.000820688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003581253,0.0040746,0.9462665,0.006322182,0.005550073,0.003915144,0.0000229927,0.001008764,0.02925846],"genre_scores_gemma":[0.578846,0.03299276,0.2115899,0.0381958,0.004740193,0.01943408,0.001365543,0.0006417851,0.112194],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7346766,"threshold_uncertainty_score":0.9997014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007350985463917005,"score_gpt":0.2085620307928912,"score_spread":0.2012110453289742,"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."}}