{"id":"W1965173328","doi":"10.1109/vetecf.2010.5594120","title":"The Impact of Fading on the Outage Probability in Cognitive Radio Networks","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Fading; Rayleigh fading; Log-distance path loss model; Node (physics); Poisson point process; Cognitive radio; Shadow mapping; Interference (communication); Computer science; Fading distribution; Gaussian; Coverage probability; Path loss; Monte Carlo method; Algorithm; Poisson distribution; Mathematics; Statistics; Telecommunications; Wireless; Physics; Artificial intelligence; Decoding methods","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":[0.0003371889,0.00008118212,0.00009090187,0.00001931878,0.0000411577,0.00001449521,0.00009007044,0.00004951486,0.00003436221],"category_scores_gemma":[0.0002067017,0.00004010295,0.00004104301,0.0001374188,0.00004186666,0.00006478408,0.00001125787,0.0002457166,0.000002617064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004822686,"about_ca_system_score_gemma":0.000007708944,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004427818,"about_ca_topic_score_gemma":0.0002216139,"domain_scores_codex":[0.9995429,0.0000296761,0.0001634566,0.00007515926,0.00004635965,0.0001424605],"domain_scores_gemma":[0.9992294,0.0005108874,0.00003071741,0.0001782152,0.00003239544,0.00001836016],"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":[0.000009154007,0.000007945142,0.002604578,0.000003675744,0.00001318253,2.199867e-7,0.0002450508,0.9942491,0.0005680344,0.0009607603,0.00005892311,0.001279352],"study_design_scores_gemma":[0.0001943204,0.0000280416,0.00673721,0.00003343428,0.000002823765,0.000001399643,0.0001880129,0.9910279,0.001150543,0.0005431898,0.00001109706,0.00008205435],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7886801,0.00004220176,0.1928137,0.00002808994,0.0002423745,0.0007663228,0.000003993405,0.0001033649,0.01731983],"genre_scores_gemma":[0.9996379,0.000007954101,0.000213923,0.000003211502,0.00003574604,0.00002776313,0.000001461687,0.00001307521,0.00005897169],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2109578,"threshold_uncertainty_score":0.1635351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01298091994209136,"score_gpt":0.2546691606980715,"score_spread":0.2416882407559801,"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."}}