A 21.8b sub-100μHz 1/f corner 2.4μV-offset programmable-gain read-out IC for bridge measurement systems
Bibliographic record
Abstract
High-resolution read-out integrated circuits (ROICs) are often used in DC measurement systems such as bridge transducers. Since these typically output small-amplitude signals with a bandwidth of a few hertz, a highly linear gain ROIC is required with a resolution above 20b [1,2]. In previous work, high-precision instrumentation amplifiers (IAs) followed by analog-to-digital converters (ADCs) were reported [1-4]. However, IA topologies based on switched-capacitor (SC) or multiple operational amplifiers (opamps) suffer from a poor power-noise tradeoff due to noise folding [2], or the number of amplifiers [3], respectively. Current-feedback IAs (CFIAs) are more power-efficient, but require highly linear feedback resistors [4,5]. This drawback can be addressed by capacitively-coupled IAs (CCIAs), which are even more power efficient [1].
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.056 | 0.023 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".