{"id":"W2152330832","doi":"10.1109/iscas.1989.100439","title":"Continuous-time analog adaptive recursive filters","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Adaptive Filtering Techniques","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Adaptive filter; Analogue filter; Analogue electronics; Electronic circuit; Filtering theory; Electronic engineering; Algorithm; Digital filter; Filter (signal processing); Engineering; Electrical engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007486412,0.000184442,0.0001959113,0.00008184035,0.00003269433,0.00001404412,0.0001248603,0.00006779611,0.0005421233],"category_scores_gemma":[0.00005186384,0.0001845737,0.00005760192,0.0001337672,0.00004838044,0.0001609863,0.00001783907,0.000142057,0.0002508397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009651982,"about_ca_system_score_gemma":0.0000075426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003324027,"about_ca_topic_score_gemma":0.000001659902,"domain_scores_codex":[0.9992526,0.00002678162,0.0001539502,0.0001845609,0.00009408072,0.0002880256],"domain_scores_gemma":[0.999563,0.00005784751,0.00002244716,0.0002342646,0.00004651846,0.00007593095],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001117634,0.0001332034,0.0009046647,0.00008959834,0.0007537865,0.000289847,0.001216243,0.03726022,0.2822412,0.4855832,0.1513803,0.04003602],"study_design_scores_gemma":[0.0008182377,0.0004599294,0.0006997953,0.0001455853,0.00004252932,0.00007287899,0.0003912587,0.01131607,0.754526,0.04483026,0.1850067,0.001690718],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00679693,0.0001896212,0.7075289,0.00002684294,0.0001894533,0.0002847529,0.00002146753,0.002620107,0.2823419],"genre_scores_gemma":[0.6936992,0.00004143017,0.300963,0.0001087775,0.00006126571,0.00005745758,0.000009090031,0.00009268305,0.004967107],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6869023,"threshold_uncertainty_score":0.7526696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008538598506033983,"score_gpt":0.1993743691091795,"score_spread":0.1908357706031455,"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."}}