{"id":"W2554124467","doi":"10.1109/netwks.2016.7751168","title":"Adaptive consistency for distributed SDN controllers","year":2016,"lang":"en","type":"article","venue":"","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Scalability; Consistency (knowledge bases); Controller (irrigation); Distributed computing; Context (archaeology); Adaptive control; Software-defined networking; Strong consistency; Adaptive system; Control (management); Artificial intelligence","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":[0.0001368713,0.0001051024,0.0001637913,0.00002859241,0.00009726495,0.00004626062,0.0003794275,0.00004981602,0.00004003532],"category_scores_gemma":[0.0001186438,0.00005956598,0.00009932071,0.0001349867,0.00005091563,0.0001996415,0.00007864973,0.00002656463,0.00005274721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003104152,"about_ca_system_score_gemma":0.00005723102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000919632,"about_ca_topic_score_gemma":0.000009855921,"domain_scores_codex":[0.9991347,0.00002112866,0.0001629299,0.0002858425,0.0001075297,0.0002878876],"domain_scores_gemma":[0.9986508,0.0007489198,0.00005466996,0.0003300087,0.0001227191,0.00009281922],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008261449,0.00005353447,0.0007697135,0.000003115626,0.0000687185,0.000006002837,0.00004338628,0.00003276031,0.0001498944,0.7599593,0.09152236,0.1473085],"study_design_scores_gemma":[0.03077431,0.002630641,0.0139334,0.0002615089,0.0001037228,0.00006026775,0.0001768941,0.2429924,0.003436616,0.3247937,0.3783819,0.002454549],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0002486363,0.00009757197,0.9926613,0.004004525,0.0003223784,0.0002528116,0.00003642354,0.0002801609,0.002096187],"genre_scores_gemma":[0.9473413,0.00001393987,0.0501371,0.0008300575,0.00009166713,0.00007684989,0.000003500349,0.000008033765,0.001497499],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9470927,"threshold_uncertainty_score":0.242903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02115256989057507,"score_gpt":0.2264228941663816,"score_spread":0.2052703242758065,"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."}}