{"id":"W2122981288","doi":"10.1109/lcn.2008.4664297","title":"Detecting changes in the Hurst parameter","year":2008,"lang":"en","type":"article","venue":"","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Hurst exponent; Computer science; Variance (accounting); Estimation theory; Wavelet; Detrended fluctuation analysis; Moving average; Rescaled range; Bandwidth (computing); Algorithm; Mathematics; Statistics; Artificial intelligence","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":[0.0002068648,0.0000520811,0.00005689666,0.00003266928,0.00009520646,0.00003915785,0.0004540753,0.00002171774,0.00001386928],"category_scores_gemma":[0.00002370049,0.00003171237,0.00001965473,0.0002270393,0.00002137743,0.00008843065,0.00003405728,0.00008939896,0.00003745235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006010123,"about_ca_system_score_gemma":0.0000116363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001296904,"about_ca_topic_score_gemma":0.0002038085,"domain_scores_codex":[0.9994615,0.00005911566,0.00006877666,0.0001375112,0.0001154575,0.0001576835],"domain_scores_gemma":[0.999501,0.000218694,0.00001837903,0.0002307311,0.00001263822,0.00001859259],"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":[0.000002489648,0.00002969755,0.002316745,0.000001097642,0.00000410767,0.00005608376,0.002246419,0.0001758894,0.00002948428,0.01806911,0.001362829,0.975706],"study_design_scores_gemma":[0.001342074,0.0002713221,0.03393697,0.00002530933,0.000006648117,0.0005201047,0.0006032353,0.9247144,0.0005921456,0.002759487,0.03468805,0.0005402433],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3597382,0.0002827212,0.5981763,0.02356335,0.0004710056,0.0002966225,1.411605e-7,0.0003326349,0.01713901],"genre_scores_gemma":[0.9934015,0.00001092986,0.003542333,0.002647722,0.00007591072,0.00002030278,6.9511e-8,0.000001800183,0.000299427],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9751658,"threshold_uncertainty_score":0.1293193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02714766989299202,"score_gpt":0.2221097802839098,"score_spread":0.1949621103909178,"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."}}