{"id":"W2153016179","doi":"10.1109/twc.2013.032113.120652","title":"Relay Selection and Resource Allocation for Multi-User Cooperative OFDMA Networks","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":125,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Relay; Subcarrier; Resource allocation; Subgradient method; Orthogonal frequency-division multiple access; Quality of service; Throughput; Frequency-division multiple access; Computer network; Telecommunications link; Mathematical optimization; Optimization problem; Orthogonal frequency-division multiplexing; Power (physics); Wireless; Telecommunications; Algorithm; Mathematics; Channel (broadcasting)","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0003131172,0.0002355785,0.0002232561,0.0001955277,0.001725128,0.0003256955,0.001386368,0.0001417759,0.00003155309],"category_scores_gemma":[0.00001543634,0.0002400212,0.00008788611,0.0007645876,0.0001597469,0.0007858154,0.00003842957,0.0005059104,0.0000283476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001060895,"about_ca_system_score_gemma":0.00006581876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004650362,"about_ca_topic_score_gemma":0.0005310734,"domain_scores_codex":[0.9983234,0.0004371951,0.0004048103,0.0004098779,0.0001384599,0.000286239],"domain_scores_gemma":[0.9968558,0.0006558992,0.0001437976,0.001655215,0.000550282,0.0001389822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000343117,0.001281612,0.0001050295,0.00002636711,0.0002431612,1.602947e-7,0.00315495,0.1634144,0.009129513,0.1143639,0.003140084,0.7051066],"study_design_scores_gemma":[0.0006587518,0.00009520868,0.0004018286,0.0000648951,0.00002353869,0.00000492669,0.0001019707,0.9852391,0.002387073,0.00003382711,0.0107129,0.0002759459],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004129028,0.0005554256,0.9859703,0.007617045,0.0001288853,0.001137565,0.00000743877,0.0003193473,0.0001350007],"genre_scores_gemma":[0.9198711,0.004474708,0.0711139,0.0007649601,0.00002513229,0.002154382,0.00001776112,0.00003120389,0.001546878],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.915742,"threshold_uncertainty_score":0.9995745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04995692058762505,"score_gpt":0.293572103782212,"score_spread":0.243615183194587,"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."}}