{"id":"W2027329806","doi":"10.1109/iswcs.2010.5624370","title":"Distributed selection of sensing nodes in cognitive radio networks","year":2010,"lang":"en","type":"article","venue":"","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Communications Research Centre Canada","funders":"","keywords":"Cognitive radio; Computer science; Node (physics); Reliability (semiconductor); Cluster analysis; Selection (genetic algorithm); Shadow (psychology); Computer network; Affinity propagation; Fading; Distributed computing; Wireless sensor network; Data mining; Wireless; Artificial intelligence; Telecommunications; Engineering; Fuzzy clustering","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":[0.000272267,0.0001180392,0.0001936921,0.0001213525,0.00007004748,0.00006989109,0.000127877,0.00008738258,0.0000226081],"category_scores_gemma":[0.00007761596,0.0001126328,0.00005250534,0.0008277633,0.00006237735,0.0002441295,0.00006431928,0.0003456403,0.000001728182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002415184,"about_ca_system_score_gemma":0.00003805969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001424294,"about_ca_topic_score_gemma":0.001087376,"domain_scores_codex":[0.9990015,0.00005702256,0.0002351805,0.0002877729,0.0001299304,0.0002885688],"domain_scores_gemma":[0.999294,0.0002847122,0.00008326361,0.0001320442,0.0001479853,0.00005800229],"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":[0.000114092,0.0003195938,0.06844846,0.00001950222,0.0001101562,0.0001357488,0.000844916,0.007535849,0.03638191,0.04497187,0.0006323584,0.8404855],"study_design_scores_gemma":[0.0003941815,0.00003290671,0.04808268,0.00004503547,0.000005801523,0.00007300244,0.00002974837,0.9431415,0.00735441,0.0006459415,0.00004290482,0.0001519124],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3181723,0.0000160104,0.6796187,0.00009228038,0.0002398347,0.00008052319,9.361416e-7,0.00006546555,0.00171396],"genre_scores_gemma":[0.9865059,0.000009527657,0.01325453,0.00006278969,0.0001297416,5.201467e-7,0.000006281844,0.000006805977,0.00002385297],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9356056,"threshold_uncertainty_score":0.4593031,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01042242881993508,"score_gpt":0.2381402185890358,"score_spread":0.2277177897691007,"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."}}