{"id":"W1981066887","doi":"10.1109/tpwrd.2013.2273942","title":"A Markov-Middleton Model for Bursty Impulsive Noise: Modeling and Receiver Design","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Power Delivery","topic":"Power Line Communications and Noise","field":"Engineering","cited_by":111,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec; McGill University","funders":"","keywords":"Impulse noise; Markov chain; Noise (video); Computer science; Markov process; Probability density function; Markov model; Probability distribution; Electronic engineering; Control theory (sociology); Algorithm; Mathematics; Statistics; Engineering; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001186817,0.0002477238,0.0002090247,0.0001939168,0.0002134902,0.00006547642,0.0002052512,0.0001373586,0.00008692939],"category_scores_gemma":[0.000004026067,0.0002557901,0.0001186868,0.000137326,0.00004034568,0.0004198366,0.000002747699,0.0002626453,0.00004990789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000909381,"about_ca_system_score_gemma":0.00003162888,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004937062,"about_ca_topic_score_gemma":0.00001264587,"domain_scores_codex":[0.9990003,0.00003097955,0.0002788755,0.000255139,0.000117249,0.0003174573],"domain_scores_gemma":[0.9990368,0.0001542297,0.00002630386,0.0004875025,0.0001535981,0.0001414989],"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":[0.00004767855,0.00006571055,6.767919e-7,0.00002374761,0.00007419454,4.970659e-7,0.0004489788,0.981564,0.005329058,0.00001345615,0.001304521,0.01112749],"study_design_scores_gemma":[0.0005212217,0.00006600309,0.000007285904,0.00004238191,0.00005265724,0.000005866943,0.00007615743,0.9958182,0.002536383,0.0004042874,0.000173895,0.0002956627],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07316815,0.0004750692,0.9246132,0.0001286242,0.0002661182,0.0006537657,0.00006675114,0.0002483433,0.0003799396],"genre_scores_gemma":[0.9659486,0.0009936537,0.03193298,0.0001341895,0.00001427512,0.0003853165,0.000005258903,0.0000663762,0.0005193723],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8927804,"threshold_uncertainty_score":0.9999894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02428125817501451,"score_gpt":0.2196457009501802,"score_spread":0.1953644427751657,"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."}}