{"id":"W2170621841","doi":"10.1109/tsp.2004.832011","title":"Characterization of Nonuniform Perfect-Reconstruction Filterbanks Using Unit-Step Signal","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Digital Filter Design and Implementation","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Mathematics; Decimation; Signal reconstruction; Generalization; Signal processing; Filter bank; Algorithm; Applied mathematics; Mathematical analysis; Filter (signal processing); Computer science; Digital signal processing","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":[0.0001515573,0.0002026958,0.0001931338,0.0003495895,0.0002977955,0.0002661237,0.0002833154,0.00007919469,0.00005935249],"category_scores_gemma":[8.944303e-7,0.0002087528,0.00009464687,0.0006911175,0.00006989088,0.002807426,0.000003078074,0.000174626,0.00001326613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001252624,"about_ca_system_score_gemma":0.0002494461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003197509,"about_ca_topic_score_gemma":0.000007767351,"domain_scores_codex":[0.9985437,0.00004016507,0.0004497351,0.0003406305,0.0003582284,0.0002675232],"domain_scores_gemma":[0.9992716,0.00002515228,0.000243926,0.0001784186,0.0001926701,0.00008820081],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003064528,0.0001273878,0.00001331106,0.00006083172,0.00001707016,0.000002490984,0.0005271915,0.007784042,0.5204088,0.000196784,4.149148e-7,0.470831],"study_design_scores_gemma":[0.0008296084,0.0003097177,0.0001336508,0.0002775678,0.00002977165,0.000112317,0.00009517493,0.1632668,0.8340528,0.0005881333,0.0000257037,0.0002787942],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.229056,0.000005661546,0.7701831,0.00004016209,0.0001732194,0.0001729277,0.00001658585,0.0000993369,0.0002530009],"genre_scores_gemma":[0.9754549,0.000003284788,0.02431421,0.0001030309,0.00004251423,0.0000119308,0.000009010644,0.00001847807,0.00004259662],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.746399,"threshold_uncertainty_score":0.8512694,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03746049418671007,"score_gpt":0.2665234116628261,"score_spread":0.229062917476116,"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."}}