{"id":"W1937293228","doi":"10.1109/iscas.1988.15041","title":"A design technique for recursive linear time-varying digital filters","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Computer science; Filter (signal processing); Computational complexity theory; Algorithm; Digital filter; Time complexity; Mathematical optimization; Mathematics","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":[0.000111829,0.0001891698,0.0001626317,0.0000873468,0.00004400012,0.00002991087,0.0001299027,0.00008528397,0.00005726457],"category_scores_gemma":[0.00013298,0.0001918115,0.00006300787,0.0001179139,0.0000272944,0.0002963434,0.00001777774,0.0001078551,0.00003950184],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009056859,"about_ca_system_score_gemma":0.00001197771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.790705e-7,"about_ca_topic_score_gemma":3.836284e-8,"domain_scores_codex":[0.9992684,0.00001266271,0.0001676389,0.0001907668,0.00007096562,0.0002896389],"domain_scores_gemma":[0.9995056,0.0001511205,0.0000224676,0.0002122517,0.00004830991,0.00006024306],"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":[0.0000736202,0.00006667757,0.0000128978,0.0001463308,0.0001308578,0.0000231086,0.0002203105,0.07137197,0.8924502,0.009418077,0.01839208,0.007693923],"study_design_scores_gemma":[0.0001698378,0.0001340305,6.480283e-7,0.00005618283,0.000006005148,0.00002118263,0.000009641712,0.01295729,0.955523,0.01195824,0.01882251,0.0003414515],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0000931403,0.00002986925,0.9846632,0.000009745469,0.00005312667,0.0009046828,0.00001873633,0.001602582,0.01262496],"genre_scores_gemma":[0.05284579,0.000008434938,0.9455788,0.00003164892,0.0000301016,0.0004909669,0.00001150181,0.0000876488,0.0009151276],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.06307284,"threshold_uncertainty_score":0.7821846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0226727234411074,"score_gpt":0.244453179742317,"score_spread":0.2217804563012096,"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."}}