{"id":"W4403981008","doi":"10.1145/3646547.3688453","title":"Replication: \"Taking a long look at QUIC\"","year":2024,"lang":"en","type":"article","venue":"","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Replication (statistics); Biology; Virology","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01897484,0.001151454,0.0009973785,0.002513862,0.006106006,0.008963956,0.004893451,0.00738896,0.03233217],"category_scores_gemma":[0.0966655,0.001125355,0.0007616448,0.00293588,0.004984648,0.02513331,0.009495974,0.01073415,0.03103708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004082748,"about_ca_system_score_gemma":0.0101512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02273829,"about_ca_topic_score_gemma":0.01708801,"domain_scores_codex":[0.9819613,0.005132121,0.0008797027,0.001529631,0.009040286,0.001457022],"domain_scores_gemma":[0.9283481,0.008833637,0.001988487,0.01825059,0.03682507,0.005754132],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001298099,0.00003197409,0.001012343,0.0001814803,0.00001584519,0.0001842719,0.0009049783,0.0002289488,0.002028098,0.03729738,0.8742186,0.0837663],"study_design_scores_gemma":[0.00001804251,0.00005179257,0.0003559509,0.0001968831,0.00001152386,0.0002446416,0.0002957344,0.0005665036,0.001139372,0.009263479,0.9877819,0.00007424825],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.007800994,0.0122118,0.1734606,0.431769,0.1117023,0.0006998926,0.003011831,0.05412102,0.2052228],"genre_scores_gemma":[0.1166525,0.009745284,0.1415033,0.276984,0.04238709,0.0011649,0.005830752,0.03364046,0.3720916],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9810252,"threshold_uncertainty_score":0.1081619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01711476553751389,"score_gpt":0.2597504159866373,"score_spread":0.2426356504491234,"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."}}