{"id":"W1543863768","doi":"10.5281/zenodo.38921","title":"Performance Of Noise-Shaping In Oversampled Filter Banks","year":2005,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Digital Filter Design and Implementation","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Filter bank; Filter (signal processing); Noise (video); Computer science; Root-raised-cosine filter; Filter design; Low-pass filter; Electronic engineering; Algorithm; Acoustics; Engineering; Physics; 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":[0.001207237,0.0007817794,0.0004502769,0.0003532395,0.00033095,0.001033585,0.0003295254,0.001240564,0.002103407],"category_scores_gemma":[0.00566234,0.0002511602,0.0002645424,0.0002514985,0.0004306148,0.0005508581,0.0005024524,0.0004270186,0.0005081851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004251206,"about_ca_system_score_gemma":0.0005219307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001115176,"about_ca_topic_score_gemma":0.000821333,"domain_scores_codex":[0.999177,0.0002486521,0.00004698656,0.0001008476,0.0003053891,0.0001211356],"domain_scores_gemma":[0.9949174,0.003794724,0.0002355783,0.0003126065,0.0006366082,0.0001030912],"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":[0.01351643,0.0003042126,0.004782602,0.0005017756,0.0002653883,0.0005987374,0.0005126653,0.2831018,0.280332,0.01052655,0.001377875,0.40418],"study_design_scores_gemma":[0.0001143581,0.0009140117,0.002991123,0.00005583998,0.0001311191,0.0005659495,0.00007486895,0.8462642,0.1436835,0.003571481,0.001590157,0.00004332958],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5777079,0.001700122,0.4121879,0.0002797788,0.0001432501,0.00003180787,0.0001154298,0.001511432,0.006322338],"genre_scores_gemma":[0.9652659,0.0003445763,0.03226602,0.00008943422,0.00004254237,0.00001809952,0.000132424,0.000075946,0.001764867],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002103407,"threshold_uncertainty_score":0.007036626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0648486822041949,"score_gpt":0.2603986182707971,"score_spread":0.1955499360666022,"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."}}