{"id":"W2021123566","doi":"10.1016/j.comcom.2014.12.004","title":"Resource allocation in multi-relay multi-user OFDM systems for heterogeneous traffic","year":2014,"lang":"en","type":"article","venue":"Computer Communications","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"National Natural Science Foundation of China","keywords":"Computer science; Subgradient method; Relay; Resource allocation; Subcarrier; Mathematical optimization; Quality of service; Transmitter power output; Transmission (telecommunications); Optimization problem; Computer network; Power (physics); Orthogonal frequency-division multiplexing; Algorithm; Telecommunications; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008914031,0.0004396704,0.0007978118,0.0003372485,0.0005568924,0.001052473,0.0008941789,0.0005637355,0.001700067],"category_scores_gemma":[0.002855586,0.0003337484,0.0002371744,0.0006383194,0.000541416,0.0009697395,0.0008319594,0.0004666857,0.0002385112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008105031,"about_ca_system_score_gemma":0.000485426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001500882,"about_ca_topic_score_gemma":0.002737253,"domain_scores_codex":[0.9995362,0.0001870075,0.00002033083,0.00007016736,0.00007176403,0.0001146162],"domain_scores_gemma":[0.9987686,0.0008758755,0.0000828294,0.00008298421,0.0001419635,0.00004770921],"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":[0.0005170088,0.0001286771,0.0008497412,0.0001470468,0.0000793019,0.0003918442,0.0001800173,0.8729469,0.01615029,0.03400952,0.001917489,0.07268215],"study_design_scores_gemma":[0.00001379872,0.00003872258,0.0001684035,0.00000450979,0.00001340481,0.00004124947,0.00002435237,0.9944172,0.001018151,0.003986285,0.0002662114,0.000007726721],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1616494,0.0014606,0.8284417,0.0004277673,0.00009243123,0.00005914961,0.0001002076,0.0001607062,0.007607966],"genre_scores_gemma":[0.969971,0.000294983,0.02830795,0.00004771157,0.00004482934,0.00004177645,0.00002690544,0.00001998302,0.001244728],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001700067,"threshold_uncertainty_score":0.005880654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09055135908521074,"score_gpt":0.3130213031296813,"score_spread":0.2224699440444706,"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."}}