{"id":"W4416655090","doi":"10.1145/3769699.3771586","title":"Towards Unsupervised Drift Detection in Programmable Data-Planes","year":2025,"lang":"","type":"article","venue":"","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Concept drift; Divergence (linguistics); Dual (grammatical number); Unsupervised learning; Pattern recognition (psychology); Novelty detection; Tracking (education); Artificial neural 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.001371041,0.0004055337,0.0004555741,0.0007137994,0.0001770925,0.001100997,0.005419632,0.0002854942,0.0001034834],"category_scores_gemma":[0.00025028,0.0004053693,0.00005161368,0.002615166,0.0001511563,0.002238318,0.004263113,0.0004500397,0.00008189314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001425488,"about_ca_system_score_gemma":0.0005921601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004236968,"about_ca_topic_score_gemma":0.003083917,"domain_scores_codex":[0.9961547,0.0002265564,0.0007740335,0.001630378,0.0004281539,0.0007862019],"domain_scores_gemma":[0.9953108,0.0001147626,0.0001199903,0.004212019,0.0001276944,0.0001147057],"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":[0.00002711316,0.000266312,0.0009558115,0.0001104388,0.00003350717,0.00004674359,0.0001898084,0.000003456278,0.0003370811,0.008166212,0.005855201,0.9840083],"study_design_scores_gemma":[0.001495512,0.0005541045,0.004407065,0.0007117628,0.00007682238,0.00004813879,0.0002773124,0.6762186,0.06316872,0.008508784,0.2434689,0.001064368],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005616534,0.0005213885,0.9452183,0.002705413,0.001426902,0.001342642,0.000127251,0.001611631,0.04142995],"genre_scores_gemma":[0.7088886,0.0002974626,0.2867961,0.000746892,0.00008164946,0.0001307558,0.0002827132,0.00002570471,0.00275007],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.982944,"threshold_uncertainty_score":0.9999615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03580633752380173,"score_gpt":0.3098929665713542,"score_spread":0.2740866290475525,"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."}}