{"id":"W2103235808","doi":"10.1109/iscas.1992.230376","title":"Median-based offset cancellation circuit technique","year":2003,"lang":"en","type":"article","venue":"","topic":"Analog and Mixed-Signal Circuit Design","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Integrator; Offset (computer science); Computer science; Ideal (ethics); Electronic circuit; DC bias; SIGNAL (programming language); Control theory (sociology); Electrical engineering; Engineering; Telecommunications; Artificial intelligence; Bandwidth (computing); Voltage","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":[0.0001573682,0.0001021182,0.0001002576,0.0000754901,0.00003322096,0.00001185625,0.00005867065,0.00008770142,0.0006794064],"category_scores_gemma":[0.00001855486,0.0001008677,0.00003836363,0.0001574466,0.00001605393,0.00004309315,9.309799e-7,0.00009596891,0.0001109316],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007002018,"about_ca_system_score_gemma":0.00004243198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000196746,"about_ca_topic_score_gemma":0.00003079211,"domain_scores_codex":[0.9994573,0.00002411541,0.0001294022,0.0001067352,0.0001054319,0.0001769965],"domain_scores_gemma":[0.9997219,0.00003095279,0.00001239996,0.0001390008,0.00002566079,0.00007005293],"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":[0.000004526563,0.00005964197,0.00184393,0.0001973919,0.00005631113,0.00004331759,0.0001576596,0.06701103,0.2822946,0.5628327,0.05333938,0.03215946],"study_design_scores_gemma":[0.0008628161,0.00008839896,0.0004235792,0.0000655999,0.00004858145,0.00002888468,0.00008311683,0.02086433,0.7280837,0.05529092,0.193164,0.0009960432],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003853666,0.0001227933,0.8162816,0.000002828489,0.0001106624,0.0001416989,0.00000310547,0.0003541214,0.1825979],"genre_scores_gemma":[0.99877,0.00001013471,0.0002955842,0.0001021753,0.00003281806,0.0000467169,0.0000117338,0.00002304086,0.0007078105],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9983846,"threshold_uncertainty_score":0.7439024,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01359044434865074,"score_gpt":0.1873673545391761,"score_spread":0.1737769101905254,"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."}}