{"id":"W1547441391","doi":"10.1109/vtcspring.2015.7145875","title":"Improving Throughput of Faster-than-Nyquist Signaling over Multiple-Access Channels","year":2015,"lang":"en","type":"article","venue":"","topic":"PAPR reduction in OFDM","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Demodulation; Throughput; Computer science; Decoding methods; Channel (broadcasting); Transmission (telecommunications); Nyquist–Shannon sampling theorem; Channel capacity; Computer network; Symbol (formal); Electronic engineering; Telecommunications; Wireless; Engineering","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":[0.00137807,0.0006144157,0.0005320434,0.000371534,0.0004478244,0.0007981011,0.0004939617,0.0004184285,0.001244375],"category_scores_gemma":[0.004384235,0.0001718874,0.0001901017,0.0005392889,0.0007817206,0.001339578,0.0006382905,0.0005157885,0.0001591943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008195373,"about_ca_system_score_gemma":0.001079242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001641945,"about_ca_topic_score_gemma":0.001761343,"domain_scores_codex":[0.999231,0.0002742019,0.00002154405,0.00007055627,0.0002733951,0.000129281],"domain_scores_gemma":[0.9982667,0.001246564,0.0001303533,0.0001539987,0.0001746982,0.00002767421],"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":[0.0002849144,0.0001031093,0.001447699,0.0001929243,0.00002963583,0.0002386491,0.0003360796,0.7656472,0.0474709,0.09562016,0.0009982673,0.08763047],"study_design_scores_gemma":[0.00000882397,0.00007694939,0.0002993993,0.00001571329,0.000008778343,0.00006093623,0.0000394768,0.980116,0.01086902,0.0075606,0.0009321601,0.00001208484],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2492641,0.001310377,0.7317818,0.0004920044,0.00009824498,0.00004882478,0.00008140648,0.0004623498,0.01646093],"genre_scores_gemma":[0.9615848,0.0004615025,0.03693098,0.00003334507,0.00004445904,0.00001990134,0.00001929728,0.00001978092,0.0008860012],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001641945,"threshold_uncertainty_score":0.007288039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04629624131677208,"score_gpt":0.2770444902133748,"score_spread":0.2307482488966027,"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."}}