{"id":"W2154621839","doi":"10.1109/tcsii.2006.873829","title":"On the implementation of input-feedforward delta-sigma modulators","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Circuits and Systems II Analog and Digital Signal Processing","topic":"Analog and Mixed-Signal Circuit Design","field":"Engineering","cited_by":79,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Feed forward; Adder; Constraint (computer-aided design); Computer science; Delta-sigma modulation; Path (computing); Control theory (sociology); Electronic engineering; Arithmetic; Control engineering; Mathematics; Artificial intelligence; Engineering; Control (management); Telecommunications; Computer network; Bandwidth (computing)","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":[0.0002298433,0.0003114203,0.0002138761,0.0002359391,0.0003001333,0.0007772549,0.0005405453,0.0004324746,0.004719762],"category_scores_gemma":[0.0005360814,0.0001765087,0.0001160883,0.0003507693,0.0002069244,0.000649307,0.000286687,0.0005369953,0.0008567648],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002816611,"about_ca_system_score_gemma":0.0003666121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004812559,"about_ca_topic_score_gemma":0.0008859319,"domain_scores_codex":[0.9998177,0.00003388226,0.00001353816,0.00001911347,0.00009445351,0.00002134145],"domain_scores_gemma":[0.9998668,0.00003836148,0.000009487348,0.00001564055,0.0000631836,0.000006417471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003148183,0.00006523194,0.0005664033,0.0007730829,0.00003160647,0.0006019091,0.0002867295,0.02139709,0.1810519,0.2576141,0.00430884,0.5329884],"study_design_scores_gemma":[0.0001226681,0.0007355743,0.001369588,0.001098239,0.0001146764,0.001768825,0.0001818308,0.2744238,0.3118947,0.07411463,0.3341121,0.0000634746],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03062132,0.005863743,0.9018533,0.0005508279,0.000544231,0.0001126932,0.0001087963,0.001019895,0.05932521],"genre_scores_gemma":[0.5251443,0.01128475,0.4301734,0.000630308,0.0003437644,0.0001134938,0.0001834626,0.00007691754,0.03204965],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004719762,"threshold_uncertainty_score":0.01578921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01243289156941676,"score_gpt":0.2123078315420665,"score_spread":0.1998749399726498,"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."}}