Signal conditioning circuit with ultra-high sensitivity and ultra-low power consumption for MEMS
Bibliographic record
Abstract
A signal conditioning circuit with ultra-high sensitivity and ultra-low power consumption is presented for the capacitive and voltage mode microelectromechanical systems (MEMS) transducers. Two different amplifiers are chopped with two different frequencies to remove their flicker noise. A low voltage high current amplifier is implemented in the 1ststage, which improves the power consumption and noise floor. The 2ndstage is composed of two parallel paths that improve SNR and provide two gain settings. The circuit is designed in a 0.13 μm CMOS technology with 0.4 V and 1.2 V supplies. The simulated power consumption is of 8.3 μW for a gain of 60 dB and 6.1 μW for a gain of 57 dB. The bandwidth is 10.5 kHz, the input-referred noise is 12.1 nV/√Hz and capacitance noise for a 100 fF capacitance transducer is of 0.0024 aF/√Hz.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".