{"id":"W1981332464","doi":"10.1145/1477942.1477960","title":"Adaptive scheduling to maximize NIC throughput in a COTS router","year":2008,"lang":"en","type":"article","venue":"","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Router; Computer science; Scheduling (production processes); Computer network; Throughput; Network interface; Embedded system; Operating system; Wireless; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009087923,0.000800267,0.0006482849,0.0005152934,0.0004580386,0.0006246199,0.001127142,0.0003637777,0.001033903],"category_scores_gemma":[0.002247313,0.0003387887,0.0001543208,0.0005917898,0.0003762509,0.0007098774,0.0005802551,0.0004513835,0.0001569744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001317933,"about_ca_system_score_gemma":0.001254835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004264424,"about_ca_topic_score_gemma":0.008291022,"domain_scores_codex":[0.9994423,0.0001489616,0.00004030093,0.0001388378,0.00009902392,0.0001306774],"domain_scores_gemma":[0.9990582,0.0002731216,0.0001713424,0.0001231183,0.0002519825,0.0001221625],"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":[0.001158764,0.0005446152,0.007214425,0.0001760652,0.0001124415,0.0004001934,0.0002883892,0.7084092,0.1184518,0.01846784,0.006010482,0.1387658],"study_design_scores_gemma":[0.00002971003,0.0001468835,0.0006042449,0.000006666844,0.00002018189,0.00004404454,0.00002129585,0.9901607,0.007275172,0.001156032,0.0005252901,0.00000982864],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5309595,0.0007686279,0.4587402,0.000429126,0.0002366783,0.0002500607,0.00007119646,0.001870083,0.006674583],"genre_scores_gemma":[0.957622,0.00009418047,0.04131892,0.00006105805,0.00003544083,0.00002893131,0.00002133233,0.00003542062,0.0007826186],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004264424,"threshold_uncertainty_score":0.009562314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03998991556557698,"score_gpt":0.2392241845337007,"score_spread":0.1992342689681237,"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."}}