{"id":"W2011163394","doi":"10.1109/glocom.2011.6133935","title":"Probabilistic Analysis of Mutual Interference in Cognitive Radio Communications","year":2011,"lang":"en","type":"article","venue":"","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Cognitive radio; Interference (communication); Computer science; Transmission (telecommunications); Co-channel interference; Computer network; Telecommunications; Channel (broadcasting); Wireless","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":[0.002615766,0.0008271636,0.000880462,0.001258743,0.0006934019,0.001445557,0.001522343,0.001010768,0.001345622],"category_scores_gemma":[0.01169894,0.0007962715,0.0008515214,0.001235023,0.001863939,0.002117954,0.001401802,0.0008978996,0.0002287174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001846337,"about_ca_system_score_gemma":0.001003147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003191386,"about_ca_topic_score_gemma":0.00248048,"domain_scores_codex":[0.9976248,0.0008222856,0.00007882909,0.0002291588,0.0009250903,0.0003197207],"domain_scores_gemma":[0.9907693,0.007080303,0.0008494236,0.0004172153,0.0007463424,0.000137348],"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":[0.0000480856,0.00001713017,0.0008942583,0.0000458511,0.00004487387,0.0001594595,0.00009228814,0.9420373,0.001076482,0.05126417,0.0002083175,0.004111757],"study_design_scores_gemma":[0.000004184978,0.00001953749,0.0004871515,0.000006818357,0.00001457942,0.00007912477,0.00001776756,0.9832647,0.0003055303,0.01557681,0.0002087423,0.00001510673],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09063458,0.0009040977,0.8983121,0.0003008929,0.00003127931,0.00005132661,0.00009908023,0.0001771539,0.0094895],"genre_scores_gemma":[0.9816878,0.0005021591,0.01593525,0.00005383182,0.00005402463,0.00006597562,0.00006003752,0.00003587984,0.001605007],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003191386,"threshold_uncertainty_score":0.01383364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0697669680034978,"score_gpt":0.285284875305701,"score_spread":0.2155179073022032,"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."}}