{"id":"W2105785674","doi":"10.1109/tcomm.2006.874006","title":"Efficient design of FMT systems","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Digital Filter Design and Implementation","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Transceiver; Electronic engineering; Iterative method; Matched filter; Channel (broadcasting); Design methods; Systems design; Filter (signal processing); Engineering; Algorithm; Wireless; Telecommunications; Computer vision","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":[0.0005363071,0.0006066126,0.0004287433,0.0003559412,0.0004051804,0.0008553385,0.0007289401,0.0008788857,0.003402377],"category_scores_gemma":[0.002030762,0.0002631349,0.0003885453,0.0003173354,0.0003456591,0.0007704555,0.0004526378,0.0006286294,0.001000489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006271555,"about_ca_system_score_gemma":0.000649401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006105455,"about_ca_topic_score_gemma":0.0008990356,"domain_scores_codex":[0.999459,0.000140653,0.00002153576,0.00007005979,0.0002640113,0.00004477433],"domain_scores_gemma":[0.9995058,0.0001718847,0.00006254001,0.00006936643,0.0001705122,0.00001987912],"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":[0.0004743204,0.00008073421,0.0006984083,0.0004131838,0.0001026109,0.0002400461,0.0002557503,0.2622605,0.1522752,0.09680301,0.004231062,0.4821652],"study_design_scores_gemma":[0.00008283179,0.0003279018,0.000385692,0.00003998461,0.000030664,0.0002744722,0.0000353502,0.934253,0.04081916,0.01115024,0.01257019,0.00003051923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004640596,0.00009516346,0.9925169,0.00004780421,0.00002558038,0.0000433534,0.00002286525,0.000221953,0.002385745],"genre_scores_gemma":[0.3232358,0.0003262568,0.6710921,0.0001205876,0.00008824434,0.0002945211,0.0001310938,0.00008573106,0.004625697],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003402377,"threshold_uncertainty_score":0.0113821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06161142283313114,"score_gpt":0.2820327095995154,"score_spread":0.2204212867663842,"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."}}