{"id":"W2101624054","doi":"10.1109/twc.2007.05317","title":"An iterative groupwise multiuser detector for overloaded MIMO applications","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Canada Research Chairs","keywords":"Multiuser detection; Computer science; MIMO; Detector; Iterative method; Wireless; Computer network; Algorithm; Mathematical optimization; Telecommunications; Mathematics; Beamforming","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003388606,0.000368098,0.0003187034,0.0004233387,0.0008745468,0.00007913184,0.001736646,0.000238414,0.00002744949],"category_scores_gemma":[0.000005333987,0.00043268,0.0001895301,0.0006673613,0.0002706247,0.0006002793,0.000008263036,0.0006571403,0.000038744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002967436,"about_ca_system_score_gemma":0.00003326848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002359924,"about_ca_topic_score_gemma":0.0006109367,"domain_scores_codex":[0.9982265,0.00009998272,0.0006673299,0.0003486713,0.000203986,0.0004535295],"domain_scores_gemma":[0.9946047,0.0009515797,0.0001200948,0.003862168,0.0002318738,0.0002296022],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001693784,0.002337669,0.00002590453,0.0001453789,0.0003004659,0.00000100334,0.002755376,0.05978397,0.3209552,0.01364083,0.0003238254,0.599561],"study_design_scores_gemma":[0.001604669,0.0002604997,0.0002003853,0.0001236106,0.000116137,0.00001104521,0.0007587113,0.2521522,0.7056118,0.001581143,0.03634191,0.001237888],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00899439,0.0002532516,0.9853213,0.0001220147,0.000130313,0.001824286,0.0002845748,0.002284911,0.0007849649],"genre_scores_gemma":[0.8635238,0.0007453343,0.1316758,0.0001165299,0.00003959721,0.003578828,0.000105069,0.0001313027,0.0000837443],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8545294,"threshold_uncertainty_score":0.9998125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02379326473246458,"score_gpt":0.3010223177188317,"score_spread":0.2772290529863671,"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."}}