{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001309872,0.0009120817,0.000556257,0.003315023,0.0004569985,0.0008398347,0.0006587963,0.0007148539,0.0005522428],"category_scores_gemma":[0.00340777,0.0001658427,0.0005669643,0.001288097,0.0002314842,0.001424496,0.0004268887,0.0007360293,0.0004946706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006115079,"about_ca_system_score_gemma":0.0006060266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004959214,"about_ca_topic_score_gemma":0.005966278,"domain_scores_codex":[0.9995354,0.00009965912,0.00004270288,0.0001273691,0.000125452,0.00006939059],"domain_scores_gemma":[0.998301,0.0009226339,0.0002137049,0.0001407936,0.0003455385,0.00007625138],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006621271,0.002003417,0.2267869,0.0001874499,0.0001775792,0.0004608549,0.0002170606,0.2853498,0.02000257,0.002072843,0.007463066,0.4546164],"study_design_scores_gemma":[0.000005267731,0.0000864371,0.01112176,0.000009697224,0.00001000482,0.00008381207,0.00006653751,0.9841771,0.00333769,0.0006936761,0.0003979743,0.00001005272],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7644051,0.0002285367,0.2271068,0.000542807,0.00009747989,0.000255134,0.002036758,0.003156763,0.002170628],"genre_scores_gemma":[0.9247547,0.0001136389,0.07123656,0.00005762623,0.00003590763,0.00009128257,0.002748252,0.00003843995,0.0009235775],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004959214,"threshold_uncertainty_score":0.009860694,"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."}}