{"id":"W3013974404","doi":"10.1109/ccnc46108.2020.9045216","title":"On Using Flow Classification to Optimize Traffic Routing in SDN Networks","year":2020,"lang":"en","type":"article","venue":"","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Scalability; Routing (electronic design automation); Computer network; Throughput; File transfer; Cloud computing; Class (philosophy); Context (archaeology); Equal-cost multi-path routing; Distributed computing; Network packet; Static routing; Popularity; Transfer (computing); Database; Routing protocol; Operating system; Artificial intelligence","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":[0.0001888337,0.0001221594,0.0001491225,0.00006078067,0.00007310575,0.000151223,0.0004369371,0.00007037316,0.0000184606],"category_scores_gemma":[0.00007510056,0.0001129187,0.00004205669,0.0008966102,0.000007669596,0.0001749791,0.0001171062,0.0001720401,0.00003889293],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005571235,"about_ca_system_score_gemma":0.00002893882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001209096,"about_ca_topic_score_gemma":0.000009373104,"domain_scores_codex":[0.9988264,0.00004924566,0.0002345571,0.0004310501,0.0001598207,0.0002988661],"domain_scores_gemma":[0.9993477,0.000163335,0.00004499305,0.0002707431,0.0000250276,0.0001482084],"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":[0.000009875854,0.00001657986,0.0001437126,0.000001275702,0.000001978344,0.000004589242,0.0003116744,0.9419907,0.00001719319,0.005233655,0.00088819,0.05138059],"study_design_scores_gemma":[0.0002248324,0.00006075655,0.0009424488,0.00002715441,0.000001590311,0.000001360762,0.00002312268,0.9984074,0.00001211685,0.0000499657,0.0001059069,0.0001433111],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.040371,0.00002043051,0.955646,0.002774289,0.0002223797,0.0001587211,2.117708e-7,0.000272803,0.0005341756],"genre_scores_gemma":[0.8138104,0.00000314833,0.182033,0.003976945,0.0001451097,0.000005689501,0.000001452764,0.000009748911,0.00001448512],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.773613,"threshold_uncertainty_score":0.4604691,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05697351503871709,"score_gpt":0.2591390191034362,"score_spread":0.2021655040647191,"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."}}