{"id":"W3037616208","doi":"10.1109/twc.2020.3003615","title":"Multi-Antenna Two-Way Relay Based Cooperative NOMA","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"China Postdoctoral Science Foundation; Natural Sciences and Engineering Research Council of Canada; Southeast University; National Natural Science Foundation of China","keywords":"Computer science; Noma; Relay; Transmission (telecommunications); Antenna (radio); Cooperative diversity; Benchmark (surveying); Diversity gain; Reliability (semiconductor); Selection (genetic algorithm); Antenna diversity; Computer network; Wireless; Telecommunications; Power (physics); MIMO; Wireless network; Beamforming; Telecommunications link; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00009892202,0.0003814067,0.0003816823,0.0002229466,0.0006671963,0.00006516669,0.002170177,0.0001840723,0.00009132286],"category_scores_gemma":[0.00002582656,0.0004215887,0.0001686271,0.001038268,0.0004442773,0.0003415558,0.00002151297,0.001275353,0.000337107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000173241,"about_ca_system_score_gemma":0.00005442935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002343929,"about_ca_topic_score_gemma":0.0002065051,"domain_scores_codex":[0.9983603,0.0001817657,0.0005507098,0.0003392048,0.000209701,0.0003583562],"domain_scores_gemma":[0.9959587,0.0004856716,0.00009307384,0.003087573,0.0001913026,0.0001836292],"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":[0.00002642083,0.0003617845,0.00002103907,0.00003597105,0.0001212934,0.000002600576,0.0007645639,0.8964767,0.07165038,0.0008221432,0.0001982233,0.0295189],"study_design_scores_gemma":[0.001042336,0.00007383034,0.00005091713,0.00006639161,0.00002950523,0.000002437522,0.0004030557,0.9206433,0.07450561,0.00001425587,0.00272157,0.0004467429],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00856818,0.0004784784,0.9815423,0.004656349,0.0001804704,0.0005106413,0.00016671,0.003346611,0.0005502269],"genre_scores_gemma":[0.9288339,0.001406137,0.06847798,0.0005412448,0.00001239671,0.0005247274,0.00003890427,0.0001099601,0.00005476487],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9202657,"threshold_uncertainty_score":0.9998236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04588430924726003,"score_gpt":0.2771615728414337,"score_spread":0.2312772635941736,"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."}}