{"id":"W2064878266","doi":"10.1109/lsp.2013.2262939","title":"Sum-Rate Maximization for Active Channels","year":2013,"lang":"en","type":"article","venue":"IEEE Signal Processing Letters","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Maximization; Channel (broadcasting); Mathematical optimization; Power (physics); Computer science; Power gain; Signal-to-noise ratio (imaging); Mathematics; Telecommunications; Physics; Amplifier; Bandwidth (computing)","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":[0.001770272,0.001621599,0.001029816,0.0004667773,0.0004565548,0.001767242,0.001147793,0.0009732224,0.002783727],"category_scores_gemma":[0.004299494,0.0005190357,0.0005289224,0.0008858475,0.001500946,0.002243628,0.00133688,0.001453778,0.000721298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00111491,"about_ca_system_score_gemma":0.000850913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001113343,"about_ca_topic_score_gemma":0.001001507,"domain_scores_codex":[0.9986896,0.0005315208,0.00004046627,0.0001757676,0.0003500428,0.0002126654],"domain_scores_gemma":[0.9974434,0.001830462,0.0001859867,0.0001444957,0.0003256429,0.00006993263],"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":[0.0002205525,0.0001382996,0.0004384355,0.0005298487,0.0001017724,0.0002883939,0.0002403909,0.6313554,0.01544753,0.3093012,0.005308365,0.03662974],"study_design_scores_gemma":[0.00003388985,0.00007854733,0.0001568453,0.00002854258,0.00003069593,0.0001321153,0.00006200937,0.8985749,0.003933779,0.0928923,0.004057404,0.00001890067],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0164974,0.001082622,0.9691232,0.0004240086,0.00007557217,0.00004369063,0.0001158677,0.00008947209,0.01254819],"genre_scores_gemma":[0.8296887,0.003455929,0.1467195,0.0004358648,0.000361942,0.0003042603,0.0002936521,0.0001788224,0.01856127],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002783727,"threshold_uncertainty_score":0.009362221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01245420138100742,"score_gpt":0.2036852640961452,"score_spread":0.1912310627151377,"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."}}