{"id":"W2980078855","doi":"10.1109/ccece.2019.8861871","title":"Enhancing System Spectral Efficiency in Cellular Networks via Full-Duplex D2D Communications","year":2019,"lang":"en","type":"article","venue":"","topic":"Full-Duplex Wireless Communications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Spectral efficiency; Cellular network; Computer science; Stochastic geometry; Telecommunications link; Interference (communication); Software deployment; Computer network; Cellular radio; Radio resource management; Telecommunications; Electronic engineering; Base station; Wireless; Mathematics; Wireless network; Engineering; Channel (broadcasting); Statistics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003324543,0.0002361619,0.0003120077,0.0001985305,0.0001201229,0.00005900369,0.001342286,0.000150691,0.0001750088],"category_scores_gemma":[0.000007980786,0.0002559581,0.0000899382,0.0006833563,0.00005839746,0.0001815509,0.0002718347,0.0005658564,0.0006448632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003578149,"about_ca_system_score_gemma":0.00002493563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002388621,"about_ca_topic_score_gemma":0.001072746,"domain_scores_codex":[0.9984313,0.0001024808,0.0005737916,0.000231039,0.0001689515,0.0004924169],"domain_scores_gemma":[0.9970065,0.0002621013,0.00005597209,0.002533142,0.00004721608,0.00009504343],"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":[0.000002446027,0.00005060104,0.0006263931,0.00007963622,0.00001776489,0.000001622217,0.0003172161,0.9230315,0.07045042,0.004984843,0.00004930219,0.0003882804],"study_design_scores_gemma":[0.0002968335,0.00001988439,0.0008694234,0.0001213168,0.000009189039,0.000009343892,0.0005448316,0.9936417,0.00389743,0.000001591501,0.0002993873,0.000289045],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8334181,0.001600575,0.152778,0.0001016441,0.0003280677,0.0005288493,0.000002868699,0.0008732855,0.01036859],"genre_scores_gemma":[0.9923869,0.000132896,0.006999814,0.00001964589,0.00004488807,0.0000707302,0.00004795317,0.00006339539,0.0002337525],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1589688,"threshold_uncertainty_score":0.9999893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007879681251954223,"score_gpt":0.2018911453022986,"score_spread":0.1940114640503444,"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."}}