{"id":"W3177446644","doi":"10.3390/sym13071133","title":"Genetic Algorithms with Variant Particle Swarm Optimization Based Mutation for Generic Controller Placement in Software-Defined Networks","year":2021,"lang":"en","type":"article","venue":"Symmetry","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Particle swarm optimization; Controller (irrigation); Convergence (economics); Genetic algorithm; Set (abstract data type); Software-defined networking; Mathematical optimization; Distributed computing; Algorithm; Machine learning; Mathematics","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":[0.0003196534,0.000212325,0.0002825402,0.0000973999,0.0001279379,0.00019647,0.0002566026,0.0001079495,0.00001986867],"category_scores_gemma":[0.0001229754,0.0001919399,0.00007285352,0.00115021,0.0000250186,0.0002024346,0.00007146141,0.0001159232,0.000004472965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000100421,"about_ca_system_score_gemma":0.0001874902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002478224,"about_ca_topic_score_gemma":0.00002737534,"domain_scores_codex":[0.998145,0.0001179743,0.0003820213,0.0005853276,0.0002825624,0.000487055],"domain_scores_gemma":[0.9986963,0.0004405802,0.0001392585,0.0004063208,0.0002019932,0.0001155838],"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":[0.00007273598,0.0001482557,0.002515952,0.0000145755,0.00003086897,0.00008533421,0.00005031464,0.9795321,0.000009604646,0.0008290226,0.0002805192,0.01643074],"study_design_scores_gemma":[0.003898871,0.0002255522,0.002492912,0.00003866763,0.00002839322,0.00002676741,0.0000238927,0.9922463,0.0002668891,0.0003379812,0.0001483362,0.0002654803],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004150981,0.000803772,0.9935896,0.000404377,0.0003441151,0.0004924614,0.000004737796,0.00017588,0.00003407103],"genre_scores_gemma":[0.3869727,0.00002091121,0.6116139,0.0009313225,0.0001215318,0.0002182572,0.00003729384,0.00002763875,0.00005650088],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3828217,"threshold_uncertainty_score":0.782708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0122224153177225,"score_gpt":0.2208871048429238,"score_spread":0.2086646895252013,"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."}}