{"id":"W2137441771","doi":"10.1109/infcom.2009.5061976","title":"Controlling False Alarm/Discovery Rates in Online Internet Traffic Flow Classification","year":2009,"lang":"en","type":"article","venue":"","topic":"Internet Traffic Analysis and Secure E-voting","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Traffic classification; Preprocessor; Network packet; Constant false alarm rate; The Internet; Classifier (UML); False alarm; False positive rate; Data mining; Artificial intelligence; Machine learning; Computer network","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":[0.01673534,0.000999645,0.001546354,0.002027033,0.000834291,0.002085433,0.002256135,0.002044413,0.0005886214],"category_scores_gemma":[0.08373759,0.0007129171,0.0005666564,0.001006932,0.001783131,0.004002044,0.001461381,0.002135267,0.000409431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001648481,"about_ca_system_score_gemma":0.001735035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001716271,"about_ca_topic_score_gemma":0.00181287,"domain_scores_codex":[0.9899544,0.004549386,0.0005730956,0.00141691,0.002649815,0.00085641],"domain_scores_gemma":[0.8670634,0.1101326,0.008495191,0.006799933,0.006581346,0.0009274199],"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":[0.002857261,0.0005911125,0.04034918,0.0001564125,0.0001537639,0.0003172899,0.0004635781,0.3987734,0.01802575,0.01527213,0.002240902,0.5207993],"study_design_scores_gemma":[0.00004083968,0.0001476572,0.001710429,0.000009722343,0.00002056474,0.0001427105,0.00003684849,0.9809543,0.009709042,0.007002932,0.0001999902,0.00002496872],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1894973,0.0003156712,0.8068804,0.0004279552,0.00004953459,0.00009288135,0.00006315025,0.001642894,0.001030238],"genre_scores_gemma":[0.8819041,0.00007968265,0.1170043,0.0001642537,0.00007763796,0.00006284904,0.00008744028,0.00008054752,0.0005392683],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01673534,"threshold_uncertainty_score":0.08850604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01987448525195771,"score_gpt":0.2602775012105207,"score_spread":0.240403015958563,"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."}}