Noise analysis of fault tolerant active pixel sensors
Why this work is in the frame
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Bibliographic record
Abstract
As digital imagers grow in pixel count and area, the ability to correct for pixel defects becomes more important. A fault tolerant active pixel sensor (APS) has previously been designed and fabricated that can correct for stuck high and stuck low defects. Analyses of the pixel noise for a standard APS and a fault tolerant APS are presented that consider reset noise, photocurrent shot noise, dark current shot noise, transistor thermal noise, transistor flicker noise, operational amplifier noise, and feedback resistor thermal noise. Under worst case conditions (no illumination), the noise of the fault tolerant APS is 1.106 /spl times/ more than a standard APS. At a typical illumination level, the fault tolerant APS noise is nearly unchanged to that of a standard APS. Previous research has shown that the fault tolerant APS is more sensitive than a standard APS, thus the overall signal-to-noise ratio of the fault tolerant APS should be greater than the standard APS except under very low light conditions.
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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 | 0.001 |
| Science and technology studies | 0.000 | 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 it