{"id":"W4388625507","doi":"10.1145/3626111.3628182","title":"Harnessing ML For Network Protocol Assessment","year":2023,"lang":"en","type":"article","venue":"","topic":"Machine Learning and Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Protocol (science); Process (computing); Network congestion; Distributed computing; Communications protocol; Network simulation; Machine learning; Artificial intelligence; Computer network; Operating system","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":[0.0005500833,0.00007039196,0.00008147869,0.00003755917,0.000214703,0.0002215223,0.000353544,0.00002325264,0.00002293351],"category_scores_gemma":[0.00001777838,0.00005439538,0.00004324537,0.0004031067,0.00000775169,0.0001414539,0.0001571924,0.00008149019,0.00006228171],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001202677,"about_ca_system_score_gemma":0.00005209399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008482077,"about_ca_topic_score_gemma":0.000001108209,"domain_scores_codex":[0.9992059,0.00003718693,0.0001147543,0.0002313408,0.0001371263,0.0002736294],"domain_scores_gemma":[0.9995433,0.0001015222,0.00004036056,0.0002385281,0.00003010459,0.00004615472],"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":[0.000003673236,0.00004205023,0.002782039,0.00008110143,0.00001546754,0.000007751154,0.0001542749,0.02022696,0.00009020497,0.1857044,0.08452601,0.7063661],"study_design_scores_gemma":[0.0002431385,0.00004759444,0.002824976,0.0000133272,6.898156e-7,0.0000012254,0.000004635376,0.8010387,0.00002646902,0.006026619,0.1896925,0.00008011326],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00003664278,5.498192e-7,0.9731711,0.001916203,0.0002529149,0.01494674,2.083938e-7,0.0007792512,0.008896383],"genre_scores_gemma":[0.003153285,1.697421e-7,0.8770574,0.0005194186,0.00063187,0.1030924,0.000004448164,0.00001519967,0.01552573],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7808117,"threshold_uncertainty_score":0.2218179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02648761047414976,"score_gpt":0.367661214310515,"score_spread":0.3411736038363652,"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."}}