{"id":"W3099360436","doi":"10.1109/ojcoms.2020.3038197","title":"SWIPT-Enabled Cooperative NOMA With <i>m</i>th Best Relay Selection","year":2020,"lang":"en","type":"article","venue":"IEEE Open Journal of the Communications Society","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; Carleton University","funders":"National Natural Science Foundation of China","keywords":"Relay; Noma; Pairwise error probability; Computer science; Wireless; Selection (genetic algorithm); Scheduling (production processes); Maximum power transfer theorem; Relay channel; Diversity gain; Bit error rate; Computer network; Pairwise comparison; Channel (broadcasting); Power (physics); Telecommunications; Mathematical optimization; MIMO; Mathematics; Artificial intelligence; Telecommunications link","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":[0.0007182248,0.0009988077,0.000840303,0.000371338,0.0006251741,0.0008668847,0.0006444216,0.0006877643,0.0006221913],"category_scores_gemma":[0.001828892,0.0002588404,0.0006087588,0.0007689972,0.000894692,0.0009613594,0.001180545,0.0005083917,0.0002879249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003082246,"about_ca_system_score_gemma":0.0004833042,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005078062,"about_ca_topic_score_gemma":0.001097095,"domain_scores_codex":[0.9994306,0.0002361908,0.00003273285,0.0000920261,0.0001242137,0.00008416545],"domain_scores_gemma":[0.9990731,0.0004825802,0.0001605143,0.0001243658,0.0001194948,0.00003993512],"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":[0.0008026743,0.0002198362,0.004737407,0.0008929433,0.0003230979,0.004298699,0.000865193,0.6370825,0.1299932,0.0756458,0.002514532,0.1426241],"study_design_scores_gemma":[0.00002708224,0.0005885895,0.0006690156,0.00004214613,0.00009094339,0.001910048,0.0001815683,0.9539335,0.0227065,0.01764941,0.002161628,0.00003945572],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1135291,0.001227962,0.8718857,0.0003426979,0.0001545733,0.00008990159,0.0001389839,0.0002747934,0.01235639],"genre_scores_gemma":[0.9308138,0.0005602235,0.06688812,0.0001076121,0.00005238569,0.00007056933,0.00003733959,0.000013531,0.00145637],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009988077,"threshold_uncertainty_score":0.003798366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04695263775007236,"score_gpt":0.2752111896495337,"score_spread":0.2282585518994614,"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."}}