{"id":"W2145537813","doi":"10.1049/iet-com.2008.0406","title":"Performance of spatially multiplexed MC-CDM with zero-forcing unified successive interference cancellation detection","year":2009,"lang":"en","type":"article","venue":"IET Communications","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"MIMO; Orthogonal frequency-division multiplexing; Subcarrier; Multiplexing; Single antenna interference cancellation; Ergodic theory; Spatial multiplexing; Mathematics; Minimum mean square error; Topology (electrical circuits); Computer science; Electronic engineering; Algorithm; Control theory (sociology); Detector; Telecommunications; Statistics; Engineering","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":[0.0001115738,0.0001646881,0.0001986737,0.0001543847,0.0001972771,0.00002166921,0.0009228563,0.0000792784,0.000006943962],"category_scores_gemma":[0.00003493971,0.0001684519,0.00003310019,0.0004189191,0.0001216158,0.0004003692,0.00009200544,0.0003221886,0.000003966394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001351683,"about_ca_system_score_gemma":0.00003154456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008369773,"about_ca_topic_score_gemma":0.0005906129,"domain_scores_codex":[0.999132,0.00006522779,0.0003839831,0.0001266409,0.0001281721,0.0001639676],"domain_scores_gemma":[0.9975533,0.000169734,0.0001920476,0.001795676,0.0002455834,0.00004365102],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000984939,0.0001253666,0.002018993,0.00009082799,0.00005633946,3.128567e-7,0.001965681,0.2627646,0.4992418,0.002303627,0.00003609011,0.2312978],"study_design_scores_gemma":[0.0003966967,0.0002360842,0.007591926,0.0003107431,0.00002390502,0.000003686481,0.00008853281,0.6255822,0.3645142,0.0003921455,0.000543426,0.0003165336],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4925621,0.0005360523,0.4950572,0.0003557797,0.00006362738,0.0006721559,0.00001688356,0.001212168,0.009523984],"genre_scores_gemma":[0.9575026,0.0012048,0.04109448,0.00002387022,0.000008548296,0.0000664703,0.00004525856,0.00002509002,0.00002890695],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4649405,"threshold_uncertainty_score":0.6869268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01663430341207487,"score_gpt":0.2487425559209803,"score_spread":0.2321082525089054,"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."}}