{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007661076,0.0004652935,0.0003848479,0.000212219,0.0002543819,0.0005592885,0.0003928613,0.0005481777,0.0005755702],"category_scores_gemma":[0.003227988,0.0003002583,0.0001932478,0.0002923671,0.0005775542,0.0006469807,0.0003312995,0.000296238,0.0003984462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000392851,"about_ca_system_score_gemma":0.0002964256,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006244754,"about_ca_topic_score_gemma":0.0006960164,"domain_scores_codex":[0.9990349,0.0003846665,0.00003340709,0.0001159211,0.0003569141,0.00007420415],"domain_scores_gemma":[0.9987397,0.0008162498,0.0001084537,0.0000671218,0.0002460673,0.00002245412],"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":[0.0006043972,0.00007990207,0.002092354,0.0002164984,0.00006982907,0.0002739878,0.0002400495,0.7401754,0.05260539,0.05742231,0.001077069,0.1451428],"study_design_scores_gemma":[0.00002422209,0.0001673671,0.0002816024,0.000012301,0.00001943379,0.00009681282,0.00001622913,0.9750463,0.0170967,0.006149544,0.001079396,0.00001013181],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05196605,0.0005930016,0.9436285,0.00008046741,0.00002793039,0.00001513038,0.00002223397,0.0002435566,0.003423013],"genre_scores_gemma":[0.8368568,0.0007110115,0.1587487,0.0001140163,0.0001217768,0.00004966095,0.00005079307,0.00004362177,0.003303455],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0007661076,"threshold_uncertainty_score":0.004051626,"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."}}