{"id":"W3014813176","doi":"10.1109/icc42927.2021.9500258","title":"An Early Benchmark of Quality of Experience Between HTTP/2 and HTTP/3 using Lighthouse","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Benchmark (surveying); Computer network; Hypertext Transfer Protocol; Implementation; Metric (unit); Latency (audio); Protocol (science); Throughput; Quality of experience; Operating system; Quality of service; Telecommunications; The Internet; Engineering; Software 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":[0.004642593,0.0004176383,0.0003914467,0.001546963,0.0003326607,0.001201833,0.0006485695,0.0007441874,0.001119703],"category_scores_gemma":[0.02259395,0.0001413139,0.0001894179,0.001905979,0.0004810718,0.001824612,0.0008663693,0.000856708,0.000483401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007484501,"about_ca_system_score_gemma":0.0004886204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003986045,"about_ca_topic_score_gemma":0.003514453,"domain_scores_codex":[0.9941494,0.001530733,0.0003460492,0.000573185,0.002897686,0.0005028261],"domain_scores_gemma":[0.9763243,0.01044359,0.001635047,0.002318516,0.008201715,0.001076909],"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":[0.005029716,0.002868977,0.3639316,0.001490515,0.0004599947,0.0007474316,0.005387942,0.03602298,0.05200741,0.01813967,0.03160351,0.4823102],"study_design_scores_gemma":[0.0001352635,0.006587357,0.7425801,0.0003161904,0.0001701156,0.000740007,0.004116877,0.1307095,0.06897075,0.006633007,0.03876747,0.0002733705],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9693009,0.0008226364,0.01222639,0.0002568745,0.0001023126,0.0001271643,0.00179773,0.001141939,0.01422406],"genre_scores_gemma":[0.9940161,0.0001070634,0.003241999,0.00005310601,0.00002218129,0.00003084152,0.001590406,0.00008191896,0.0008564353],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004642593,"threshold_uncertainty_score":0.02455264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05636416313564693,"score_gpt":0.3272032747184145,"score_spread":0.2708391115827676,"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."}}