{"id":"W2070997326","doi":"10.1109/vtcfall.2014.6965860","title":"Aggregate Interference Analysis for Interweave Cognitive Networks","year":2014,"lang":"en","type":"article","venue":"","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Nakagami distribution; Fading; Cognitive radio; Interference (communication); Computer science; Path loss; Moment-generating function; Poisson distribution; Transmitter power output; Topology (electrical circuits); Node (physics); Shadow mapping; Aggregate (composite); Telecommunications; Algorithm; Computer network; Random variable; Mathematics; Transmitter; Statistics; Wireless; Physics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001594419,0.000956745,0.0007209562,0.001442345,0.0005424907,0.001035198,0.001101825,0.0006852481,0.001371585],"category_scores_gemma":[0.006148352,0.0002953179,0.0008101565,0.001180385,0.001136789,0.001578343,0.001186415,0.0007535162,0.0002377413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00137496,"about_ca_system_score_gemma":0.0008175179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004407192,"about_ca_topic_score_gemma":0.002030154,"domain_scores_codex":[0.9986942,0.0002893482,0.00004058174,0.0001160438,0.0006322679,0.0002275536],"domain_scores_gemma":[0.9967275,0.00216972,0.0003363442,0.0001730353,0.0005070132,0.00008635783],"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":[0.00003705143,0.00002708188,0.0008359824,0.00005656408,0.000050921,0.000226679,0.0001198161,0.9046867,0.00275818,0.0814617,0.0004846393,0.009254617],"study_design_scores_gemma":[0.000001489894,0.00001034117,0.0002238512,0.000004652804,0.000006676279,0.00005306304,0.00002576222,0.9816019,0.0003945063,0.01742637,0.0002458937,0.000005430334],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04443138,0.0008501213,0.9472893,0.0001535321,0.00003715147,0.00002027326,0.00005850892,0.00009738368,0.007062273],"genre_scores_gemma":[0.9701581,0.001286492,0.02456083,0.0001353769,0.0001270371,0.00007708822,0.00008926473,0.00005572955,0.003509992],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004407192,"threshold_uncertainty_score":0.009976089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01600918303749376,"score_gpt":0.2481576473228882,"score_spread":0.2321484642853944,"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."}}