{"id":"W2133787935","doi":"10.1109/iscas.2009.5118255","title":"Sampled-data IIR filtering using time-mode signal processing circuits","year":2009,"lang":"en","type":"article","venue":"","topic":"Advancements in PLL and VCO Technologies","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Infinite impulse response; Computer science; Filter (signal processing); Chebyshev filter; Time domain; Electronic engineering; Signal processing; Electronic circuit; 2D Filters; Low-pass filter; SIGNAL (programming language); Filter design; Digital signal processing; Digital filter; Computer hardware; Engineering; Electrical 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":[0.00005859788,0.000164153,0.0001558178,0.00008049957,0.00009613733,0.00005693492,0.0004557447,0.00007277809,0.0001549925],"category_scores_gemma":[0.00001468229,0.0001551486,0.00001840411,0.0001762521,0.00002599701,0.000542674,0.000116934,0.0001374567,0.00002841363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005320842,"about_ca_system_score_gemma":0.00001199952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003434008,"about_ca_topic_score_gemma":0.000001377329,"domain_scores_codex":[0.9991165,0.000003760404,0.0001908476,0.0002359499,0.0001283959,0.0003244852],"domain_scores_gemma":[0.9995156,0.00001559668,0.00002506083,0.0003906546,0.00001809722,0.0000350032],"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":[0.000001863119,0.00002294938,0.00005589914,0.00004329497,0.0000181057,0.000008478074,0.00005396655,0.04441465,0.1794575,0.0001361539,0.0008964828,0.7748907],"study_design_scores_gemma":[0.0001786899,0.00002824294,0.00008381245,0.00008488961,0.00001506587,0.00001805633,0.00006372374,0.9666564,0.02582192,0.002097442,0.004612144,0.000339592],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05448361,0.0005514025,0.9317788,0.00005301075,0.00009028168,0.0001356668,0.00002590063,0.002581641,0.01029966],"genre_scores_gemma":[0.9393049,0.00002705213,0.06030343,0.00006285233,0.0000843147,0.000001977801,0.00002744906,0.00002302184,0.0001649349],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9222417,"threshold_uncertainty_score":0.6326775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05719849490633589,"score_gpt":0.3065426756056257,"score_spread":0.2493441806992898,"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."}}