{"id":"W2802262217","doi":"10.1109/iscas.2018.8351362","title":"Implementation of a Cache-Based IPv6 Lookup System with Hashing","year":2018,"lang":"en","type":"article","venue":"","topic":"Network Packet Processing and Optimization","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Cache; Cache algorithms; Hash function; Page cache; Packet forwarding; Cache pollution; Cache invalidation; Bottleneck; Hash table; Parallel computing; CPU cache; Cache coloring; Throughput; Table (database); Computer network; Network packet; Operating system; Embedded system; Database","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":[0.0001829158,0.00005850611,0.00007313582,0.0000522222,0.0000850037,0.00008636824,0.0001890521,0.00001865341,0.0000104167],"category_scores_gemma":[0.000001849515,0.00004379905,0.00001180854,0.0003084951,0.00003087829,0.0002792467,0.00002322862,0.00002323412,0.000006339114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000274705,"about_ca_system_score_gemma":0.0001011079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001638257,"about_ca_topic_score_gemma":0.0001863569,"domain_scores_codex":[0.9994141,0.00002645064,0.0001322242,0.0001557031,0.0001557535,0.0001158049],"domain_scores_gemma":[0.9994968,0.00001834761,0.0001039527,0.0001908626,0.0001608898,0.0000291173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001425432,0.0002523536,0.07389338,0.001042694,0.0001530487,0.00002064534,0.01323356,0.07485896,0.00303473,0.1677151,0.005404595,0.6602484],"study_design_scores_gemma":[0.0006608756,0.0002857347,0.0007991426,0.0001114903,0.000009293684,0.000005718357,0.00054292,0.9630253,0.03428221,0.00003148658,0.0001194118,0.0001263882],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02860814,0.000006907119,0.9665936,0.0001182118,0.0000629646,0.0000697881,2.66892e-7,0.0001367086,0.00440336],"genre_scores_gemma":[0.8360773,2.340162e-7,0.1637596,0.00006581534,0.00004090614,0.000003903965,0.000001702915,0.000003881252,0.00004659896],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8881664,"threshold_uncertainty_score":0.1786073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009603134004372214,"score_gpt":0.2510464586910404,"score_spread":0.2414433246866682,"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."}}