{"id":"W2103127503","doi":"10.1109/ssap.1996.534838","title":"Impulsive noise modeling with stable distributions in fading environments","year":2002,"lang":"en","type":"article","venue":"","topic":"Power Line Communications and Noise","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Fading; Poisson distribution; Rayleigh fading; Noise (video); Interference (communication); Computer science; Statistical physics; Mathematics; Series (stratigraphy); Algorithm; Statistics; Telecommunications; Physics; 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":[0.00003242852,0.00007631247,0.00007285465,0.00005082646,0.00004773894,0.00001448096,0.0001093978,0.00002378154,0.0002034045],"category_scores_gemma":[0.000003875109,0.00006896343,0.00001399247,0.0001344875,0.00001037057,0.0001428465,0.00002949749,0.0001061469,0.00005916747],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008222272,"about_ca_system_score_gemma":0.000001675549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003622417,"about_ca_topic_score_gemma":0.00004934028,"domain_scores_codex":[0.9995813,0.000006844492,0.000115142,0.00007594794,0.00005360715,0.0001671103],"domain_scores_gemma":[0.9996683,0.00001355538,0.000007109446,0.0002646809,0.000004381011,0.00004196744],"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":[0.000001754572,0.00007855171,0.001414075,0.000006309067,0.00001669132,0.000003458086,0.0002591147,0.9933578,0.002346048,0.0007658619,0.0003013242,0.001449035],"study_design_scores_gemma":[0.0002043234,0.000006591051,0.0003063771,0.00001499669,0.000004207603,0.000001760591,0.00007211039,0.9969557,0.0005892442,0.00007279632,0.001665024,0.0001068741],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5626597,0.0006489858,0.4095718,0.00008222548,0.00002854444,0.000126939,0.00002186471,0.0001260021,0.02673395],"genre_scores_gemma":[0.9963913,0.000315414,0.002975706,0.000007638278,0.000006748446,0.00002216789,0.00001636513,0.00001297274,0.0002517045],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4337316,"threshold_uncertainty_score":0.2812247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01535195649975946,"score_gpt":0.1957352945596264,"score_spread":0.1803833380598669,"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."}}