{"id":"W2990643636","doi":"10.1109/pimrc.2019.8904423","title":"GFDM-Modulated Full-Duplex Cognitive Radio Networks in the Presence of RF Impairments","year":2019,"lang":"en","type":"article","venue":"","topic":"Full-Duplex Wireless Communications","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Transmitter; Cognitive radio; Frequency offset; Orthogonal frequency-division multiplexing; Phase noise; Electronic engineering; Multiplexing; Computer science; Radio frequency; Telecommunications; Physics; Topology (electrical circuits); Wireless; Electrical engineering; Channel (broadcasting); 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002254805,0.0001391145,0.0001862736,0.0000777625,0.00002901352,0.00002083585,0.000565942,0.00008606917,0.0002741354],"category_scores_gemma":[0.00004003817,0.0001088404,0.0000517663,0.0004545022,0.00005371922,0.0001405028,0.00008405559,0.0002726723,0.00007441141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003831584,"about_ca_system_score_gemma":0.0000129992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001340597,"about_ca_topic_score_gemma":0.000159422,"domain_scores_codex":[0.9990701,0.00007867084,0.0002925541,0.00013609,0.0001705276,0.0002520692],"domain_scores_gemma":[0.9987735,0.0004765047,0.0000419506,0.0006168418,0.00005791572,0.00003328378],"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":[0.00001726092,0.00006321184,0.003033183,0.00001974061,0.0000400552,0.000001724332,0.000888264,0.9911556,0.003398728,0.0001829825,0.0004471563,0.0007520664],"study_design_scores_gemma":[0.0005335908,0.0000501934,0.03791007,0.00007709878,0.000009057616,0.000006751543,0.0005154277,0.9602256,0.0004489768,0.0000031374,0.0000928055,0.0001272289],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941143,0.0003260557,0.002211837,0.00007260867,0.0001113136,0.0005730444,0.000009155699,0.0001201382,0.002461549],"genre_scores_gemma":[0.9991309,0.0001300214,0.00036525,0.0000388454,0.00001606464,0.00004503356,0.00003946072,0.00002415489,0.00021028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03487689,"threshold_uncertainty_score":0.4438381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009715955539010248,"score_gpt":0.2272988287097742,"score_spread":0.217582873170764,"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."}}