{"id":"W2116773029","doi":"10.1109/vtcf.2006.381","title":"An Efficient Detector for Spatially Multiplexed MC-CDM Communications","year":2006,"lang":"en","type":"article","venue":"IEEE Vehicular Technology Conference","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Multiplexing; Detector; Diversity gain; Spatial multiplexing; MIMO; Computer science; Transmitter; Electronic engineering; Frequency-division multiplexing; Antenna diversity; Code division multiple access; Orthogonal frequency-division multiplexing; Telecommunications; Engineering; Wireless; Beamforming; Channel (broadcasting)","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":[0.0008001218,0.0004375262,0.0006816403,0.0006144093,0.0004006116,0.0005651634,0.0006822766,0.0008211758,0.000943732],"category_scores_gemma":[0.001610101,0.0002987062,0.0002380528,0.0004691343,0.0005593786,0.0009049312,0.0006313515,0.0008249988,0.000489682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003980142,"about_ca_system_score_gemma":0.0007217464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002322203,"about_ca_topic_score_gemma":0.0005757975,"domain_scores_codex":[0.9992452,0.0001979207,0.00002637041,0.00009380146,0.0003933804,0.0000434588],"domain_scores_gemma":[0.9991096,0.0003945821,0.0001056556,0.0001111616,0.0002348094,0.00004431323],"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":[0.0006202407,0.0002556076,0.002448332,0.0003457477,0.0001676914,0.0002506317,0.0001631602,0.1112604,0.3084692,0.07563017,0.004140223,0.4962487],"study_design_scores_gemma":[0.0000575159,0.0002905535,0.000458376,0.00001755331,0.0000414745,0.0007130356,0.00001592547,0.8843552,0.09695619,0.007008492,0.01003794,0.00004771975],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009285544,0.0003908483,0.9894012,0.0001127133,0.00004392492,0.00003278468,0.00001917204,0.0001283223,0.0005854839],"genre_scores_gemma":[0.1376755,0.0002932713,0.8600792,0.0001766664,0.00006307981,0.00006778449,0.00003808753,0.00001360962,0.001592798],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.000943732,"threshold_uncertainty_score":0.004231453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0169898321771352,"score_gpt":0.2642804813995367,"score_spread":0.2472906492224015,"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."}}