{"id":"W2111637073","doi":"10.1109/vetecs.2003.1208864","title":"Fast symbol timing recovery techniques for burst-mode digital demodulators","year":2004,"lang":"en","type":"article","venue":"","topic":"Analog and Mixed-Signal Circuit Design","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Additive white Gaussian noise; Burst mode (computing); Computer science; Symbol rate; Demodulation; Interpolation (computer graphics); Feed forward; Preamble; Algorithm; Electronic engineering; Real-time computing; White noise; Bit error rate; Decoding methods; Telecommunications; Frame (networking); Engineering; Channel (broadcasting)","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":[],"consensus_categories":[],"category_scores_codex":[0.00006060909,0.0001643306,0.0001696244,0.00009157136,0.00005930424,0.00007259542,0.0001152534,0.0001050241,0.00001620299],"category_scores_gemma":[0.00001973766,0.0001580483,0.0001142532,0.00009150912,0.00002002442,0.0003259165,0.000009895785,0.00008801146,0.00004290947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001183163,"about_ca_system_score_gemma":0.00002195286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001681457,"about_ca_topic_score_gemma":0.000006331516,"domain_scores_codex":[0.9992667,0.000002760865,0.0001815774,0.0001689233,0.00009211968,0.0002878505],"domain_scores_gemma":[0.9996856,0.00003972277,0.00001657004,0.0001466963,0.0000305715,0.00008079302],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00005636691,0.0001919359,0.0005611417,0.0004794233,0.0005207996,0.00004667201,0.0007737505,0.1904309,0.06610216,0.1645691,0.01407484,0.562193],"study_design_scores_gemma":[0.002382469,0.0009742185,0.0003504362,0.0005690166,0.0002111473,0.0001683776,0.001236406,0.0175521,0.5854237,0.3646409,0.02306882,0.003422408],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01879522,0.00008280808,0.9600486,0.000007059049,0.0001191356,0.0002564494,0.00002943945,0.0009995271,0.01966178],"genre_scores_gemma":[0.9973485,0.00001351343,0.001756922,0.00005961899,0.0001361295,0.00005016269,0.00002512452,0.00005379198,0.0005561652],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9785534,"threshold_uncertainty_score":0.6445022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01193659448075941,"score_gpt":0.221062013478356,"score_spread":0.2091254189975966,"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."}}