{"id":"W1978954881","doi":"10.1109/tvt.2012.2203327","title":"Joint Space-Time Parameter Estimation for Multicarrier CDMA Systems","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Direction-of-Arrival Estimation Techniques","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Smoothing; Subcarrier; Multipath propagation; Covariance matrix; Code division multiple access; Algorithm; Computer science; Decorrelation; Joint (building); Electronic engineering; Orthogonal frequency-division multiplexing; Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003802032,0.0002129919,0.0003385185,0.0007774872,0.0001591266,0.00004725041,0.0004246003,0.0003529769,0.00001351815],"category_scores_gemma":[0.00008416747,0.0002094545,0.0001655639,0.0007149531,0.0001402127,0.0005644953,0.00000584779,0.0002309744,0.00008962515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001169097,"about_ca_system_score_gemma":0.00003870588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001733781,"about_ca_topic_score_gemma":7.125773e-7,"domain_scores_codex":[0.9985219,0.00006381692,0.0004417044,0.0003412573,0.0002487931,0.0003824888],"domain_scores_gemma":[0.998522,0.0001793558,0.0002012417,0.0007920279,0.0002138312,0.00009150839],"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":[0.00008041522,0.002155727,0.00009188582,0.0004720969,0.0006017877,0.000007399477,0.0009136517,0.1130333,0.2155981,0.1916839,0.001415845,0.4739458],"study_design_scores_gemma":[0.0002429065,0.0001808566,0.00002147335,0.00005265222,0.00003656961,0.00003884872,0.00001338461,0.5112239,0.4848045,0.002349016,0.0008516043,0.0001844032],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01425893,0.00007098126,0.9818228,0.0007201072,0.0007614873,0.000849356,0.00001514894,0.001418195,0.00008294078],"genre_scores_gemma":[0.6991035,0.000005118853,0.300264,0.00002683988,0.00001419203,0.0004565801,0.000001727015,0.00001966862,0.0001083616],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6848446,"threshold_uncertainty_score":0.8541307,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01793113486942034,"score_gpt":0.2582527950253429,"score_spread":0.2403216601559225,"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."}}