{"id":"W1559816512","doi":"10.1109/isspit.2003.1341183","title":"Optimum probing for downlink vector channel estimation","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Channel (broadcasting); Telecommunications link; Minimum mean square error; Computer science; Least-squares function approximation; Mean squared error; Algorithm; 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":[0.001051678,0.0004393359,0.0007062844,0.0002479673,0.0002335737,0.0005260051,0.0003321733,0.00059659,0.00095829],"category_scores_gemma":[0.007711456,0.0003311129,0.0001780289,0.0004122136,0.0005826637,0.001332335,0.0006930405,0.0005326901,0.000255672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002966786,"about_ca_system_score_gemma":0.0003934265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005325312,"about_ca_topic_score_gemma":0.0004621782,"domain_scores_codex":[0.9984794,0.0008921561,0.00003861585,0.0001389536,0.0003281627,0.0001227574],"domain_scores_gemma":[0.9971402,0.002270907,0.0001753485,0.0001695434,0.000206154,0.00003790438],"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":[0.001569014,0.0001040808,0.002589277,0.0002689922,0.00006988354,0.0001541929,0.0002004947,0.6139779,0.05990765,0.03287144,0.002723416,0.2855637],"study_design_scores_gemma":[0.00001823858,0.0001180149,0.0002604759,0.000007344232,0.000008270702,0.00008571654,0.00001383553,0.9894267,0.005409494,0.004092521,0.0005483732,0.00001090669],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04523652,0.000813179,0.9520478,0.0002064788,0.00003820334,0.0000181304,0.0000418729,0.0003389391,0.001258831],"genre_scores_gemma":[0.8615769,0.000484123,0.1367222,0.0001041987,0.00006512956,0.00004209064,0.00006131826,0.00003585481,0.000908294],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001051678,"threshold_uncertainty_score":0.005561888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01554365991082893,"score_gpt":0.2582428037675153,"score_spread":0.2426991438566864,"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."}}