A 5-V 290- $\mu\hbox{W}$ Low-Noise Chopper-Stabilized Capacitive-Sensor Readout Circuit in 0.8- $\mu\hbox{m}$ CMOS Using a Correlated-Level-Shifting Technique
Bibliographic record
Abstract
In this brief, a low-power high-resolution readout front end intended for capacitive sensors is presented, in which the circuit uses correlated-level-shifting (CLS) and chopperstabilization (CS) techniques. CLS is a relatively new switchedcapacitor (SC) technique that is used to reduce errors from finite operational amplifier (op-amp) gain, whereas CS is a classic technique that is used to reduce the adverse effects of dc offset and low-frequency noise associated with the op-amp. In this brief, the capacitive sensor is physically emulated by a pair of on-chip differential variable capacitors that are in the femtofarad range. The proposed front end is designed in a 0.8-μm CMOS technology and consumes 290 μW from a single 5-V supply. The readout circuit achieves a capacitance noise floor of 0.018 aF/√Hz at 400 Hz with a sensitivity of 50 mV/fF.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".