{"id":"W2065706027","doi":"10.1109/isit.2012.6284012","title":"On the sum-capacity of Gaussian MAC with peak constraint","year":2012,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Security Techniques","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Constraint (computer-aided design); Channel (broadcasting); Gaussian; Uniqueness; Code (set theory); Computer science; Channel capacity; Topology (electrical circuits); Algorithm; Mathematics; Mathematical optimization; Telecommunications; Combinatorics; Mathematical analysis; Physics; Geometry","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":[0.003914591,0.001362308,0.001230536,0.001436514,0.0009512378,0.002386277,0.001334876,0.0009552849,0.004272438],"category_scores_gemma":[0.0181551,0.0006490895,0.0006163932,0.00167899,0.004483672,0.003917163,0.002842969,0.002092418,0.0005818429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002257232,"about_ca_system_score_gemma":0.001434984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002431926,"about_ca_topic_score_gemma":0.001157077,"domain_scores_codex":[0.9977905,0.001082654,0.00005376088,0.0001832335,0.0004838783,0.0004060126],"domain_scores_gemma":[0.984696,0.01305759,0.0004875326,0.0005692288,0.000957848,0.0002318096],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002165656,0.00004789235,0.0005006319,0.0002052026,0.00005528033,0.0002178651,0.0002608755,0.3523416,0.003341785,0.630078,0.002170276,0.01056396],"study_design_scores_gemma":[0.00001856178,0.00004586337,0.0002647715,0.00008399015,0.0000250571,0.0001124658,0.00008158924,0.7262058,0.001525579,0.2705089,0.001092626,0.0000348418],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1196065,0.003758994,0.8147361,0.002068641,0.0001751157,0.0000706847,0.0004698983,0.0003108822,0.05880314],"genre_scores_gemma":[0.9664944,0.003079298,0.02508337,0.0003952681,0.0004173207,0.0001708881,0.0001465196,0.0001516691,0.004061205],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004272438,"threshold_uncertainty_score":0.0207026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0251628732935441,"score_gpt":0.2280568128344977,"score_spread":0.2028939395409536,"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."}}