{"id":"W1626500089","doi":"10.1109/ccece.2004.1345004","title":"Kalman filtering for channel estimation in space-time coded systems","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Kalman filter; Fading; Computer science; Channel (broadcasting); Decoding methods; Doppler effect; Algorithm; Context (archaeology); Coding (social sciences); Electronic engineering; Telecommunications; Mathematics; Statistics; Artificial intelligence; Engineering","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":[0.001092288,0.0007427089,0.0007928843,0.0004469546,0.0004397708,0.000986769,0.0005055706,0.001201338,0.001615821],"category_scores_gemma":[0.004274901,0.0003411654,0.0003853539,0.0008765562,0.000853551,0.00125312,0.0005479567,0.001299178,0.0005375148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001269409,"about_ca_system_score_gemma":0.001298929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0146584,"about_ca_topic_score_gemma":0.008067679,"domain_scores_codex":[0.9994093,0.0002302246,0.00003143329,0.0000817928,0.0001904911,0.00005674777],"domain_scores_gemma":[0.9986269,0.0009966939,0.00008093653,0.00008690529,0.0001923153,0.00001630863],"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":[0.00008010618,0.00001819356,0.0005202654,0.0001775306,0.00005564776,0.00009388237,0.0001193094,0.8479804,0.002001282,0.08533878,0.001780398,0.06183416],"study_design_scores_gemma":[0.00001008556,0.00002357294,0.0001393052,0.00001780866,0.00001024933,0.00001501703,0.00001039327,0.9832091,0.0005570571,0.01457843,0.001416463,0.0000124933],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003407004,0.001782206,0.9928262,0.0002293674,0.00008558376,0.00001501382,0.00003241418,0.0001642514,0.001457875],"genre_scores_gemma":[0.7257314,0.01023818,0.2546282,0.0002558455,0.0006329735,0.0003587538,0.0003228243,0.0001054661,0.007726452],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0146584,"threshold_uncertainty_score":0.02914613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01428044008629577,"score_gpt":0.250822981014325,"score_spread":0.2365425409280292,"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."}}