{"id":"W2149945936","doi":"10.1109/vetecs.2000.851369","title":"Linear MMSE interference suppression in asynchronous random-CDMA","year":2002,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Code division multiple access; Minimum mean square error; Asynchronous communication; Computer science; Bit error rate; Spread spectrum; Wideband; Process gain; Interference (communication); Matched filter; Algorithm; Bandwidth (computing); Mathematics; Electronic engineering; Telecommunications; Statistics; Decoding methods; Engineering; Detector; Estimator","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":[0.0003994708,0.000110403,0.0001622659,0.0001737959,0.00007939358,0.0001263693,0.0022398,0.00007016308,0.0006616804],"category_scores_gemma":[0.00009318017,0.00009042785,0.00003954614,0.0005767033,0.00005929905,0.0004908574,0.0010104,0.0003543777,0.0005395265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006045468,"about_ca_system_score_gemma":0.00002215557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005952927,"about_ca_topic_score_gemma":0.00006858076,"domain_scores_codex":[0.9985138,0.0002839767,0.0002734388,0.0003101069,0.0002779136,0.000340775],"domain_scores_gemma":[0.9981651,0.0003615082,0.00004353884,0.001255709,0.00007102742,0.0001031651],"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":[0.00009551782,0.001104719,0.005866814,0.00004165512,0.00002513809,0.0000979839,0.004561914,0.009199979,0.00285855,0.02659944,0.03306812,0.9164802],"study_design_scores_gemma":[0.001045712,0.00004504833,0.0007914559,0.00004867178,3.83012e-7,0.000007344609,0.00001337718,0.9938117,0.001421342,0.0003024975,0.002387946,0.0001244716],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02562658,0.0007358049,0.9243931,0.005002489,0.0002189919,0.000366758,5.175915e-7,0.0002963861,0.04335939],"genre_scores_gemma":[0.9764006,0.0003474434,0.02154875,0.0001568101,0.00003398271,0.00003269748,0.000001189996,0.000007459727,0.001471121],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9846117,"threshold_uncertainty_score":0.7244936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04364643063662232,"score_gpt":0.2921000947384038,"score_spread":0.2484536641017814,"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."}}