{"id":"W2133431248","doi":"10.1109/twc.2012.032812.111476","title":"Resource Allocation for Two-Way AF Relaying with Receive Channel Knowledge","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Decoding methods; Multiplexing; Resource allocation; Coding (social sciences); Channel (broadcasting); Relay; Computer network; Transmitter power output; Exploit; Constraint (computer-aided design); Mathematical optimization; Upper and lower bounds; Power (physics); Algorithm; Telecommunications; Transmitter; Mathematics; Statistics","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":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0006931472,0.0002578295,0.0002405692,0.0002663685,0.00180301,0.0001390991,0.002329683,0.00009448849,0.00001335096],"category_scores_gemma":[0.00001336079,0.0002488861,0.000119212,0.00102278,0.0001820264,0.0008619532,0.00004018276,0.0005177925,0.00009103017],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001943002,"about_ca_system_score_gemma":0.00009841496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001039136,"about_ca_topic_score_gemma":0.0002702261,"domain_scores_codex":[0.9981775,0.00046539,0.0003851765,0.000333508,0.0001890537,0.0004493572],"domain_scores_gemma":[0.9948489,0.001041614,0.000173499,0.003366412,0.0003697369,0.000199825],"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":[0.0001453975,0.003444228,0.00005148662,0.00006260371,0.0003476717,3.943257e-7,0.02465045,0.01605554,0.005752614,0.235918,0.002569991,0.7110016],"study_design_scores_gemma":[0.004146656,0.0005661391,0.0004649553,0.0006964991,0.0001977455,0.00006261294,0.001518756,0.7935258,0.03267623,0.0005198403,0.1638407,0.001784086],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001459586,0.0009990096,0.9861175,0.004646372,0.0002438399,0.0007185032,0.00001229016,0.0003854343,0.005417446],"genre_scores_gemma":[0.9630943,0.0009403013,0.03368427,0.0003522172,0.00005894506,0.0009569288,0.00002479822,0.00004044091,0.000847805],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9616347,"threshold_uncertainty_score":0.9999964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06577431010897368,"score_gpt":0.3080892538285011,"score_spread":0.2423149437195274,"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."}}