{"id":"W1593533099","doi":"10.1109/vetecs.2004.1390546","title":"Joint domain localized adaptive processing for CDMA systems","year":2005,"lang":"en","type":"article","venue":"","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Telecommunications link; Code division multiple access; Beamforming; Single antenna interference cancellation; Joint (building); Interference (communication); Multiuser detection; Space-division multiple access; Adaptive beamformer; Algorithm; Computer engineering; Real-time computing; Electronic engineering; Computer network; Telecommunications; Decoding methods; Engineering; 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":[0.0002627809,0.0002856391,0.000214326,0.0002003658,0.0001776072,0.0004739589,0.0002243116,0.0004213931,0.001764081],"category_scores_gemma":[0.001017794,0.0001290547,0.0001765604,0.0003717544,0.0003427903,0.0004888134,0.000296131,0.0006455262,0.0006232665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002935636,"about_ca_system_score_gemma":0.0004645417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000938703,"about_ca_topic_score_gemma":0.001201066,"domain_scores_codex":[0.9998361,0.00006568086,0.000005031819,0.0000230449,0.00005844764,0.0000116996],"domain_scores_gemma":[0.9997268,0.0001307699,0.00002108877,0.00004655026,0.00006640227,0.000008346542],"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":[0.0001522238,0.00005743342,0.0004713768,0.0001222345,0.00003072811,0.00009451216,0.0001077194,0.4274264,0.04106965,0.08126814,0.004094093,0.4451056],"study_design_scores_gemma":[0.00001033678,0.0000432029,0.0001127069,0.000005429599,0.000004985836,0.00003681225,0.000009986762,0.9811023,0.004289332,0.01075225,0.003624676,0.000007983499],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004530026,0.0003143286,0.9936188,0.00008887098,0.00002135348,0.0000102296,0.000009309278,0.0001487826,0.001258234],"genre_scores_gemma":[0.3915973,0.001226896,0.6009696,0.0001410739,0.0001024208,0.0001113671,0.00009175897,0.00004548667,0.005714145],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001764081,"threshold_uncertainty_score":0.005901456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03287781838050877,"score_gpt":0.2796653049597593,"score_spread":0.2467874865792506,"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."}}