{"id":"W1954902203","doi":"10.1109/ccece.1996.548127","title":"Internal quantization error for triple-loop sigma-delta converters with sinusoidal excitations","year":2002,"lang":"en","type":"article","venue":"","topic":"Analog and Mixed-Signal Circuit Design","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Quantization (signal processing); Sigma; Delta-sigma modulation; Converters; Control theory (sociology); Excitation; Closed loop; Physics; Mathematics; Computer science; Algorithm; Engineering; Quantum mechanics; Artificial intelligence; Power (physics); Control 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":[0.00006328193,0.0001435486,0.0001449876,0.0001035869,0.00007139015,0.00004392402,0.0001025687,0.00005782543,0.0004054522],"category_scores_gemma":[0.00002062161,0.0001244043,0.00005861563,0.0001519447,0.0000338827,0.0001894568,0.000003537784,0.00007682029,0.00006051783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004063663,"about_ca_system_score_gemma":0.000008403868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002674541,"about_ca_topic_score_gemma":0.00007940878,"domain_scores_codex":[0.9993038,0.0000139959,0.0001912449,0.0001543703,0.0001143739,0.0002222609],"domain_scores_gemma":[0.9996299,0.00007909399,0.00002687195,0.0001130988,0.00007136088,0.00007974378],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002741388,0.0004758423,0.002816611,0.0006624423,0.001322494,0.00007454279,0.006063108,0.1533829,0.04469357,0.3115361,0.4104888,0.06820942],"study_design_scores_gemma":[0.002279977,0.0003713697,0.0002711689,0.00006753912,0.00008912174,0.00003424899,0.0007561779,0.9870629,0.002766662,0.001207026,0.004575229,0.0005186356],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007117791,0.00009277686,0.983992,0.0000286225,0.0001652761,0.0002757787,0.0000186698,0.0003110844,0.007998016],"genre_scores_gemma":[0.993505,0.000009965039,0.0007209284,0.0001448414,0.00006527102,0.00005100118,0.00003640842,0.00003982703,0.005426749],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9863872,"threshold_uncertainty_score":0.5073059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03045535053540175,"score_gpt":0.2202034206827558,"score_spread":0.1897480701473541,"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."}}