Area efficient non‐fractional binary‐weighted split‐capacitive‐array DAC for successive‐approximation‐register ADC
Bibliographic record
Abstract
An area efficient non‐fractional binary‐weighted capacitive‐array with attenuation capacitor (NFBWA) digital‐to‐analogue converter (DAC) is presented for successive‐approximation‐register ADC. Based on linearity and matching requirement, the segmentation degrees (i.e. the number of bits in each split capacitive sub‐array) are optimised to minimise the switching power and area. The proposed DAC improves the Walden figure‐of‐merit performance by 1.67 and 5.45 times, respectively, compared with that of fractional binary‐weighted capacitive‐array with attenuation capacitor (FBWA) DAC and conventional NFBWA DAC at the same unit capacitor size and linearity requirement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".