{"id":"W2767716445","doi":"10.3390/info8040141","title":"Rate Optimization of Two-Way Relaying with Wireless Information and Power Transfer","year":2017,"lang":"en","type":"article","venue":"Information","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Ministry of Science and ICT, South Korea; National Research Foundation of Korea; National Research Foundation","keywords":"Relay; Power (physics); Computer science; Maximum power transfer theorem; Wireless; Optimization problem; Transformation (genetics); Computational complexity theory; Phase (matter); Wireless power transfer; Resource allocation; Mathematical optimization; Energy (signal processing); Convex optimization; Mathematics; Regular polygon; Algorithm; Telecommunications; Computer network; Physics","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":[0.00192154,0.001901142,0.001487541,0.0005601136,0.000397889,0.001728055,0.001434202,0.001632764,0.002410588],"category_scores_gemma":[0.00391817,0.0006016842,0.0008374558,0.00119746,0.001426748,0.002047202,0.001499134,0.001392552,0.0005995878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001282583,"about_ca_system_score_gemma":0.000964221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001819281,"about_ca_topic_score_gemma":0.001097015,"domain_scores_codex":[0.999076,0.000402266,0.00003870922,0.0001629722,0.0002034435,0.0001166279],"domain_scores_gemma":[0.9982888,0.001260557,0.0001511283,0.00008902186,0.0001615252,0.00004902924],"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":[0.00006776473,0.00004505005,0.0001884064,0.000140816,0.00003835462,0.0001729361,0.0000776817,0.9405881,0.003528784,0.04271938,0.0007848993,0.01164776],"study_design_scores_gemma":[0.00001103359,0.00002770564,0.00004614931,0.000006770884,0.000009087209,0.00004086342,0.00001331716,0.9898352,0.0007769993,0.008827281,0.000396472,0.000009135511],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02174718,0.001272284,0.9684021,0.0005218167,0.00008161421,0.00004833997,0.00009377448,0.00009393747,0.007738945],"genre_scores_gemma":[0.8397227,0.003330062,0.1435829,0.000200672,0.0001720478,0.0002936283,0.0001974238,0.0001544728,0.01234603],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002410588,"threshold_uncertainty_score":0.01016217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005176552030399256,"score_gpt":0.1871109613372977,"score_spread":0.1819344093068984,"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."}}