{"id":"W2157641626","doi":"10.1109/icc.2000.853305","title":"Oversampled blind MLSDE receiver","year":2002,"lang":"en","type":"article","venue":"","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Phase-shift keying; Computer science; Oversampling; Robustness (evolution); Channel (broadcasting); Keying; Algorithm; Gaussian noise; Bit error rate; Electronic engineering; Bandwidth (computing); Telecommunications; 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":[0.001042284,0.000520594,0.00123029,0.0007171694,0.0003385938,0.0008430579,0.0006890357,0.001335953,0.002295215],"category_scores_gemma":[0.002916893,0.0003216701,0.0004965381,0.0005426272,0.0005500601,0.001305669,0.001142075,0.0008125896,0.0009764043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003513016,"about_ca_system_score_gemma":0.0008046348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005663986,"about_ca_topic_score_gemma":0.0006921118,"domain_scores_codex":[0.9987561,0.0003538583,0.0000866397,0.0002050536,0.0005118522,0.00008646933],"domain_scores_gemma":[0.9986348,0.0005035448,0.0001363006,0.0003022629,0.0003859496,0.00003718647],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008227925,0.0001234162,0.002004712,0.0004069288,0.000162285,0.0002873334,0.0002123642,0.140869,0.1469927,0.03730038,0.005821434,0.6649967],"study_design_scores_gemma":[0.00008664983,0.0002232423,0.0007449816,0.00004395017,0.00006099374,0.00115185,0.00002544089,0.9003098,0.07426371,0.009437274,0.01356544,0.00008670671],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007701848,0.0005022964,0.9894654,0.0001487047,0.00007718259,0.00002171602,0.00004969638,0.0008560184,0.001177342],"genre_scores_gemma":[0.32687,0.0006087112,0.6650402,0.0005132167,0.0001829515,0.00007545931,0.000255239,0.00006425278,0.006390019],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002295215,"threshold_uncertainty_score":0.00767827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04818190080813466,"score_gpt":0.2572451398383228,"score_spread":0.2090632390301881,"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."}}