{"id":"W2119789524","doi":"10.1109/ccece.1999.807994","title":"Optimal design of general multi-channel nonuniform transmultiplexers","year":2003,"lang":"en","type":"article","venue":"","topic":"Digital Filter Design and Implementation","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Aliasing; Computer science; Distortion (music); Channel (broadcasting); Signal reconstruction; Algorithm; Phase distortion; Limiting; Dual (grammatical number); Measure (data warehouse); Transmission (telecommunications); Signal processing; Telecommunications; Bandwidth (computing); 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001931452,0.0001024719,0.0001089145,0.00008204959,0.00003574673,0.00007042895,0.0003135428,0.00002692196,0.00003736397],"category_scores_gemma":[0.00001250596,0.0000891044,0.00005354404,0.0001948565,0.00002383457,0.0007523386,0.00001993374,0.00003204431,0.00002104509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000164997,"about_ca_system_score_gemma":0.00004717551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000199787,"about_ca_topic_score_gemma":0.000001786781,"domain_scores_codex":[0.9991577,0.00004392286,0.0002252941,0.0001961082,0.0001639783,0.0002130299],"domain_scores_gemma":[0.9995821,0.0000340097,0.00004776905,0.000210639,0.00005486016,0.00007064777],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009992433,0.001544163,0.0003308991,0.00009600216,0.000208958,0.00003739831,0.009673807,0.2117802,0.2002992,0.4986234,0.007719507,0.06958655],"study_design_scores_gemma":[0.001519486,0.0002831261,0.0002228369,0.000005977185,0.00000498201,0.00001367417,0.0001107612,0.699222,0.2969583,0.0008210587,0.0005992377,0.0002385795],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002131371,0.00001071258,0.9935777,0.00003862314,0.0001113683,0.0002088009,0.000002605706,0.00006379219,0.003855014],"genre_scores_gemma":[0.4220998,0.000003335573,0.5768103,0.0001113584,0.000004483308,0.000007887596,0.000002039358,0.000004929989,0.00095588],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4978023,"threshold_uncertainty_score":0.3633572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06441070230012141,"score_gpt":0.2768312992660678,"score_spread":0.2124205969659463,"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."}}