{"id":"W1493465688","doi":"10.1109/pacrim.2005.1517341","title":"Smart maximum-likelihood-CDMA multiuser detection","year":2005,"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 Alberta","funders":"","keywords":"Code division multiple access; Computer science; Detector; Multiuser detection; Constraint (computer-aided design); Algorithm; Maximum likelihood; Signal-to-noise ratio (imaging); Detection theory; Upper and lower bounds; Code (set theory); Computational complexity theory; Division (mathematics); Mathematics; Telecommunications; Statistics; Arithmetic; Set (abstract data type)","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":[0.0007804233,0.0004775638,0.0008073747,0.0005867718,0.0003131465,0.0007861718,0.001021355,0.0008063444,0.001489854],"category_scores_gemma":[0.003064951,0.0004647512,0.000334305,0.0005953427,0.000459143,0.00101407,0.001038384,0.0009107509,0.001042395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003369281,"about_ca_system_score_gemma":0.0008421859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003024447,"about_ca_topic_score_gemma":0.0007933692,"domain_scores_codex":[0.9993129,0.000220582,0.00002853984,0.00008158019,0.0003125726,0.00004384119],"domain_scores_gemma":[0.9989622,0.0004997232,0.0001257425,0.0001707339,0.0001957054,0.00004597546],"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":[0.0005892579,0.0001450676,0.002708589,0.0004401979,0.0001672241,0.0003197848,0.0001450841,0.1766808,0.06725876,0.06573774,0.008614697,0.6771928],"study_design_scores_gemma":[0.00005254131,0.00009109658,0.000323512,0.00001077253,0.00001610447,0.0002198536,0.00000502599,0.9776232,0.01085822,0.007722516,0.003055567,0.00002168115],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004886085,0.0002166321,0.9934509,0.00008577844,0.00003960366,0.00002376411,0.00003264146,0.0005587918,0.0007057141],"genre_scores_gemma":[0.2573196,0.0002953298,0.7393511,0.0002319522,0.00006955595,0.0001420437,0.0001807975,0.00005317951,0.002356515],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001489854,"threshold_uncertainty_score":0.004984021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02007396969400796,"score_gpt":0.2731032292079293,"score_spread":0.2530292595139214,"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."}}