{"id":"W4297917719","doi":"10.48550/arxiv.1806.04580","title":"Online VNF Placement and Chaining for Value-added Services in Content\\n Delivery Networks","year":2018,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Virtual network; Provisioning; Computer network; Chaining; Content delivery network; Control reconfiguration; Quality of service; Distributed computing; Server","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"],"consensus_categories":[],"category_scores_codex":[0.0004177441,0.000347715,0.000420192,0.0003024413,0.0001711811,0.0001713875,0.001188837,0.0002716233,0.000003885883],"category_scores_gemma":[0.00001427801,0.0003995197,0.000162738,0.0002633005,0.00008404777,0.0003199454,0.002064381,0.0004362659,0.000004395796],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001708686,"about_ca_system_score_gemma":0.00008682267,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006874963,"about_ca_topic_score_gemma":0.0004514146,"domain_scores_codex":[0.9978827,0.0001224482,0.0002774051,0.001177178,0.00008602793,0.0004543045],"domain_scores_gemma":[0.9984802,0.0001915344,0.0002582833,0.0007376768,0.0001829755,0.0001493183],"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":[0.0006161698,0.0005824561,0.0160297,0.0005343039,0.000460763,0.0003865182,0.00188077,0.9392689,0.0001385924,0.03532777,0.0003845464,0.004389479],"study_design_scores_gemma":[0.001373623,0.0001367168,0.001106661,0.000414975,0.00005939983,0.000003510757,0.0004869953,0.9944229,0.00001349694,0.00147083,0.00008905659,0.000421856],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6892436,0.0003114542,0.3090917,0.0000730927,0.0006019092,0.0004001671,0.00002575953,0.0001316751,0.0001206422],"genre_scores_gemma":[0.9969371,0.0004320739,0.00138036,0.0004517264,0.0001746175,0.000003240121,0.00006221161,0.0000191781,0.0005395025],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3077113,"threshold_uncertainty_score":0.9998457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09967209607776854,"score_gpt":0.1943283735807596,"score_spread":0.09465627750299101,"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."}}