{"id":"W2136714344","doi":"10.1109/vetecf.2005.1558996","title":"Turbo multiuser detection with integrated channel estimation for differentially coded asynchronous CDMA systems","year":2006,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Multiuser detection; Code division multiple access; Algorithm; Telecommunications link; Channel (broadcasting); Turbo; Iterative method; Decoding methods; Convolutional code; Turbo code; Asynchronous communication; Single antenna interference cancellation; 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":[0.001180258,0.0005785536,0.0005782,0.0003691345,0.000394319,0.0007304205,0.0006729192,0.001101772,0.0007102347],"category_scores_gemma":[0.004805347,0.0003730719,0.0003836401,0.0005556337,0.0009174263,0.0009830812,0.0006934891,0.0006755338,0.0002636706],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008084272,"about_ca_system_score_gemma":0.001385473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002492764,"about_ca_topic_score_gemma":0.002678102,"domain_scores_codex":[0.9990861,0.0004324392,0.00002507742,0.0000900398,0.0002873261,0.0000789691],"domain_scores_gemma":[0.9979552,0.001414086,0.000153635,0.0001197859,0.0003146981,0.00004260447],"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":[0.0001958518,0.00003449876,0.001169289,0.0001666053,0.00007727625,0.0003617838,0.0001994916,0.8590851,0.008875052,0.04773381,0.0008040741,0.08129721],"study_design_scores_gemma":[0.000009966007,0.00003587884,0.0001196664,0.000005360412,0.00001142643,0.00006406388,0.000008374447,0.9920895,0.001906957,0.005337827,0.0004019351,0.000009045562],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01068483,0.0003160956,0.988057,0.00008742043,0.00001556148,0.00001430591,0.00001154605,0.00008266861,0.0007306223],"genre_scores_gemma":[0.7343255,0.0008714505,0.2611007,0.00008795397,0.00009146551,0.00009423458,0.00007778317,0.00002833577,0.00332263],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002492764,"threshold_uncertainty_score":0.006241918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01556103181838261,"score_gpt":0.2469477778272152,"score_spread":0.2313867460088326,"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."}}