{"id":"W2132234921","doi":"10.1109/ccece.2004.1345337","title":"Adaptive soft-input soft-output multiuser detection for coded CDMA systems","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Multiuser detection; Detector; Computer science; A priori and a posteriori; Algorithm; Asynchronous communication; Code division multiple access; Control theory (sociology); Recursive least squares filter; Adaptive filter; Telecommunications; Artificial intelligence","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":[0.0006907047,0.0002880369,0.0002959644,0.00036101,0.0001944744,0.0004330839,0.0003634936,0.0003535633,0.0007196118],"category_scores_gemma":[0.003419665,0.000186623,0.0001593892,0.0003639199,0.0005581148,0.0005019754,0.0004191358,0.0003935099,0.000159375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005074597,"about_ca_system_score_gemma":0.0005675742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009971162,"about_ca_topic_score_gemma":0.001493314,"domain_scores_codex":[0.9995778,0.0001442338,0.00001741637,0.00003959199,0.0001945162,0.00002649026],"domain_scores_gemma":[0.9986344,0.0009679334,0.000115236,0.00009412863,0.0001638484,0.00002444375],"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":[0.0004233288,0.00006021546,0.001909368,0.0001460525,0.00004474586,0.0001202965,0.0001181433,0.795633,0.02307539,0.03340754,0.0007069042,0.1443551],"study_design_scores_gemma":[0.00001609925,0.00003959335,0.0002100873,0.000005799763,0.000005845468,0.00003413804,0.000006020415,0.9894465,0.004874824,0.00497792,0.0003740694,0.000009133528],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05516968,0.0003905168,0.9420894,0.0001156127,0.00003387316,0.00002604601,0.00001750826,0.000201453,0.001955956],"genre_scores_gemma":[0.8639178,0.000278859,0.1341356,0.00007154932,0.00002359505,0.00004814923,0.00002185063,0.00002004179,0.001482466],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009971162,"threshold_uncertainty_score":0.003681898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02212977524892171,"score_gpt":0.2463992807288221,"score_spread":0.2242695054799004,"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."}}