{"id":"W2470596919","doi":"10.1049/el.2016.1908","title":"Thermal noise limit for time‐domain analogue signal processing in CMOS technologies","year":2016,"lang":"en","type":"article","venue":"Electronics Letters","topic":"Advancements in PLL and VCO Technologies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"CMOS; Electronic engineering; Signal processing; Noise (video); SIGNAL (programming language); Limit (mathematics); Time domain; Voltage; Electrical engineering; Computer science; Engineering; Digital signal processing; Mathematics; Artificial intelligence","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":[0.0005778703,0.00037695,0.0004029438,0.0004431215,0.0004377407,0.00132446,0.0005001508,0.0009447622,0.002767141],"category_scores_gemma":[0.002962925,0.0002406711,0.0002860583,0.0003115299,0.0008788866,0.001369759,0.00059708,0.0009539951,0.0007653087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006843458,"about_ca_system_score_gemma":0.0003011336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003874816,"about_ca_topic_score_gemma":0.0002655965,"domain_scores_codex":[0.9992261,0.0001368898,0.00003494924,0.0001263413,0.00040432,0.00007143311],"domain_scores_gemma":[0.9985303,0.001092807,0.0001007781,0.00007300603,0.000179986,0.0000230847],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005139693,0.00009342204,0.001375883,0.001154528,0.00008847655,0.0009167047,0.0006014397,0.04930857,0.4282762,0.4130276,0.002453442,0.1021898],"study_design_scores_gemma":[0.00003633953,0.0007649493,0.002626332,0.0007677741,0.0001784864,0.004251662,0.0002917152,0.4636661,0.2936437,0.1827468,0.05085892,0.0001672837],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1163157,0.05515159,0.7352977,0.001820128,0.0009392459,0.00007620414,0.0001405328,0.0007996204,0.08945922],"genre_scores_gemma":[0.9348234,0.01190987,0.04051456,0.0005176194,0.0005413002,0.00008884809,0.00008801152,0.0001711454,0.01134518],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002767141,"threshold_uncertainty_score":0.009257019,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006129022694137249,"score_gpt":0.205306966198475,"score_spread":0.1991779435043378,"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."}}