{"id":"W2963011891","doi":"10.1109/tcomm.2019.2906307","title":"On the Performance of Network NOMA in Uplink CoMP Systems: A Stochastic Geometry Approach","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":79,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Engineering and Physical Sciences Research Council","keywords":"Noma; Telecommunications link; Base station; Stochastic geometry; Computer science; Spectral efficiency; Computer network; Bandwidth (computing); Transmission (telecommunications); Channel (broadcasting); Topology (electrical circuits); Telecommunications; Engineering; Mathematics; Electrical 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":[0.002263957,0.0021411,0.001290965,0.001279493,0.0009192594,0.001534284,0.001594168,0.0009739562,0.001179329],"category_scores_gemma":[0.007644633,0.0008033694,0.0009587461,0.00152422,0.00213808,0.001634,0.00174634,0.0009518589,0.0004517133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00221463,"about_ca_system_score_gemma":0.001402642,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004907995,"about_ca_topic_score_gemma":0.003707459,"domain_scores_codex":[0.9977895,0.001198291,0.00005715698,0.0002299201,0.0004929258,0.0002321257],"domain_scores_gemma":[0.9960556,0.002543354,0.000461724,0.0003092133,0.0005166834,0.0001133704],"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":[0.00005443377,0.00002412845,0.0005051289,0.00007241232,0.00003494262,0.0001194593,0.00004979267,0.9592427,0.001696884,0.02978489,0.000527349,0.007887889],"study_design_scores_gemma":[0.000003123286,0.00004256475,0.0001531147,0.00000633932,0.000008569627,0.00005698183,0.00001041331,0.9951989,0.000418167,0.003780459,0.0003101417,0.00001117035],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02803938,0.00139994,0.9601291,0.0003406645,0.0001082591,0.00006502756,0.000102983,0.0002569119,0.009557658],"genre_scores_gemma":[0.9269016,0.003225505,0.06708558,0.0002144431,0.0002779269,0.0001201654,0.0001164587,0.00008807158,0.00197023],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004907995,"threshold_uncertainty_score":0.01606828,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02046179298077786,"score_gpt":0.2244320215318485,"score_spread":0.2039702285510706,"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."}}