{"id":"W2119262514","doi":"10.1109/icc.1998.685171","title":"An error analysis of feedback correlation beamforming for the IS-95 reverse link","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Estimator; Beamforming; Eigenvalues and eigenvectors; Link (geometry); Computer science; Extension (predicate logic); Algorithm; Upper and lower bounds; Correlation; Perturbation (astronomy); Cramér–Rao bound; Error analysis; Mathematics; Mathematical optimization; Applied mathematics; Statistics; Telecommunications","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":[0.005009626,0.0008993358,0.0006696982,0.0007719112,0.0004785394,0.0009865002,0.0008342349,0.0007966418,0.001588717],"category_scores_gemma":[0.02354944,0.000339455,0.0004456146,0.0008265328,0.0009280046,0.001182555,0.001138258,0.0008047236,0.0003888128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001128443,"about_ca_system_score_gemma":0.001479,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004034359,"about_ca_topic_score_gemma":0.002474085,"domain_scores_codex":[0.9971681,0.0007919702,0.00007991865,0.000218602,0.001575644,0.0001657926],"domain_scores_gemma":[0.9898011,0.007201628,0.0006755068,0.0006697139,0.001579952,0.00007211367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003301802,0.00004200049,0.002755032,0.000144944,0.00006827503,0.0001267519,0.0001496592,0.8765067,0.01047867,0.03974086,0.0007346816,0.06892231],"study_design_scores_gemma":[0.000008554988,0.00007070592,0.0008046872,0.00002169458,0.00001559812,0.0000875285,0.00001800282,0.9861267,0.008534556,0.003898213,0.0003916022,0.00002214254],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04367927,0.0002482617,0.9533575,0.0002306928,0.00003394188,0.00003149258,0.00004596491,0.000224572,0.002148422],"genre_scores_gemma":[0.8330103,0.0005193205,0.1623114,0.0001113815,0.00005015879,0.0001149759,0.0001670986,0.0001263631,0.003588877],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005009626,"threshold_uncertainty_score":0.02649373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02045966387209833,"score_gpt":0.2453157585996311,"score_spread":0.2248560947275327,"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."}}