{"id":"W4400234828","doi":"10.1109/noms59830.2024.10575442","title":"Identifying IoT Devices: A Machine Learning Analysis Using Traffic Flow Metadata","year":2024,"lang":"en","type":"article","venue":"","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Solana Networks (Canada); Dalhousie University","funders":"","keywords":"Metadata; Computer science; Internet of Things; Flow (mathematics); Embedded system; World Wide Web","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":[0.0002409849,0.0001528536,0.0001890768,0.0006853286,0.00007993238,0.000394853,0.0001499013,0.00005060202,0.0002139584],"category_scores_gemma":[0.000006392861,0.0001427867,0.000163396,0.001216034,0.00001112291,0.0003820343,0.00005159126,0.0002183664,0.00003041556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006124043,"about_ca_system_score_gemma":0.000005866029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003460298,"about_ca_topic_score_gemma":0.0002229824,"domain_scores_codex":[0.9991537,0.00002326596,0.0002212351,0.0002347325,0.0001688978,0.0001982143],"domain_scores_gemma":[0.9997142,0.00002574261,0.00001157084,0.0001830483,0.00001060246,0.00005484433],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001111487,0.000009019084,0.00006990748,0.000222541,0.001807029,0.00002890935,0.0002257675,0.9254091,0.0005806983,0.0005892764,0.002043187,0.06901347],"study_design_scores_gemma":[0.00004340388,0.000004926131,0.00006477893,0.00003650175,0.0008663923,0.000003808522,0.00009914366,0.9658213,0.0001762292,0.000004862433,0.03272664,0.000151984],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01793793,0.002254473,0.9597077,0.00002085016,0.0002759545,0.00009314276,0.00000966137,0.01723416,0.002466107],"genre_scores_gemma":[0.9604536,0.0001775791,0.03856734,0.00002977975,0.00005051664,0.000008047933,0.00005665393,0.00003513705,0.0006213961],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9425156,"threshold_uncertainty_score":0.5822674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02758757706015544,"score_gpt":0.2653091209406036,"score_spread":0.2377215438804482,"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."}}