{"id":"W2973686901","doi":"10.1109/icmcis.2019.8842671","title":"Machine Learning-Based Traffic Classification of Wireless Traffic","year":2019,"lang":"en","type":"article","venue":"","topic":"Internet Traffic Analysis and Secure E-voting","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Computer science; Wireless; Computer network; Traffic classification; Artificial intelligence; Machine learning; Telecommunications; Quality of service","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":[0.001327572,0.0007733429,0.0008138585,0.002025598,0.0004495372,0.00105459,0.0009037133,0.0007993178,0.0005738537],"category_scores_gemma":[0.004819071,0.0001695531,0.0004605536,0.001180639,0.0004299521,0.00159683,0.0004815257,0.0007570249,0.000444516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008084578,"about_ca_system_score_gemma":0.0005509074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002297143,"about_ca_topic_score_gemma":0.001345796,"domain_scores_codex":[0.9989125,0.0002984585,0.00009554348,0.000192107,0.0003380398,0.0001634429],"domain_scores_gemma":[0.9979573,0.0007761691,0.0002217344,0.0002001546,0.0007836347,0.00006096452],"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":[0.0005045105,0.0005661153,0.01900945,0.0001160188,0.0001025972,0.0001993523,0.0001145546,0.4525287,0.02091351,0.007068499,0.002384799,0.4964918],"study_design_scores_gemma":[0.000002158003,0.00001843787,0.0006479899,0.000002130028,0.000004057222,0.00002076984,0.000009671664,0.9961625,0.001993862,0.001002489,0.0001311573,0.000004790393],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2793021,0.0003251155,0.7164243,0.0001741363,0.0001266802,0.0001053283,0.000145507,0.001194677,0.002202024],"genre_scores_gemma":[0.9547162,0.0001212517,0.04380265,0.00002913403,0.00004267649,0.00004068311,0.0002829685,0.00002352708,0.0009408368],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002297143,"threshold_uncertainty_score":0.00702095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01298785061015325,"score_gpt":0.2281792878746504,"score_spread":0.2151914372644972,"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."}}