{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000372631,0.0001777742,0.0003146038,0.0002151642,0.0001364943,0.0002816435,0.0004143334,0.00006023663,0.00002676954],"category_scores_gemma":[0.000114535,0.000152673,0.0002583773,0.000885171,0.00005410025,0.0002497046,0.0001826754,0.0001292721,0.00001367755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002627212,"about_ca_system_score_gemma":0.00001362014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001912256,"about_ca_topic_score_gemma":0.0002277167,"domain_scores_codex":[0.9986259,0.00008810867,0.00024276,0.0005291401,0.0001117429,0.0004023626],"domain_scores_gemma":[0.9984839,0.0007714814,0.0001085851,0.0003029826,0.0002161544,0.0001168906],"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":[0.00006350307,0.00006801019,0.002567993,0.000007811103,0.001004273,0.00001284294,0.0004031348,0.003311036,0.0000379047,0.08166605,0.0003541101,0.9105033],"study_design_scores_gemma":[0.0003381032,0.000165461,0.00208319,0.00004371493,0.0001394891,0.000008856508,0.00003633943,0.9930739,0.0004737056,0.003093328,0.0003135556,0.0002302888],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008806488,0.00006175849,0.9825413,0.0003206453,0.0002611793,0.0001738928,0.000001529313,0.0001676317,0.007665535],"genre_scores_gemma":[0.9835413,0.00001641809,0.01491469,0.0009324953,0.0002026799,0.00001353903,0.00001003022,0.000009338424,0.0003595104],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.989763,"threshold_uncertainty_score":0.6225824,"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."}}