{"id":"W2022641958","doi":"10.1109/pimrc.2010.5672047","title":"Multi-user diversity gain in uplink cognitive radio systems with spectrum sensing reliability","year":2010,"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 British Columbia","funders":"","keywords":"Telecommunications link; Cognitive radio; Scheduling (production processes); Computer science; Diversity gain; Reliability (semiconductor); Transmitter; Computer network; Base station; Channel (broadcasting); Electronic engineering; Fading; Telecommunications; Wireless; Engineering","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":[0.002681398,0.001169504,0.001289482,0.000639324,0.0005743941,0.001478487,0.0008289388,0.0009057723,0.0009847662],"category_scores_gemma":[0.01561834,0.0005177411,0.0004421106,0.000742672,0.001256917,0.001530484,0.00151956,0.0008948598,0.0001592886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001165083,"about_ca_system_score_gemma":0.0009175762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00164804,"about_ca_topic_score_gemma":0.001547263,"domain_scores_codex":[0.9980801,0.0007081677,0.0000469781,0.0001864111,0.0004354169,0.000542842],"domain_scores_gemma":[0.985031,0.01143331,0.001178656,0.0007616292,0.001269754,0.0003256499],"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":[0.000574564,0.000162432,0.00547234,0.000183126,0.0001690776,0.0007957223,0.0003362382,0.9015427,0.02035074,0.04196955,0.0004812821,0.02796212],"study_design_scores_gemma":[0.00002734666,0.0002291252,0.001389889,0.0000133553,0.00006504068,0.0003388644,0.00006672286,0.9825771,0.003116756,0.01195016,0.0001976671,0.00002789996],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5518978,0.002114536,0.4329567,0.0005605703,0.00006688504,0.00006256867,0.00009011255,0.0002707581,0.01198016],"genre_scores_gemma":[0.9946756,0.0001967081,0.004694338,0.00003514718,0.00002994469,0.00001620372,0.000008945473,0.00001091948,0.000332106],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002681398,"threshold_uncertainty_score":0.01418078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01231387390151999,"score_gpt":0.2216721334409638,"score_spread":0.2093582595394438,"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."}}