Why this work is in the frame
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Bibliographic record
Abstract
An implementation of the compressive sensing (CS) method with a CMOS image sensor is presented. The conventional three-transistor active pixel sensor (APS) structure and switched capacitor circuits are exploited to develop an analog implementation of the CS encoding in a CMOS sensor. With the analog implementation, the sensing and encoding are performed in the same time interval and making a real-time encoding process to optimize the frame rate of the imager. A block readout strategy is proposed to capture the required CS measurements for different blocks of the image, rather than the common column-row readout method. All measurement circuits are placed outside the array by this readout strategy, and the imager becomes scalable for larger array sizes. Because there is no extra in-pixel element for the CS measurement process, the fill factor of the imager is the same as its corresponding APS imager without CS. The proposed structure is designed and fabricated in 0.13- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="TeX">\(\mu \) </tex-math></inline-formula> m CMOS technology for a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="TeX">\(2\times 2\) </tex-math></inline-formula> array. The experimental results confirm the validity of the design in making monotonic and appropriate CS measurements. The functionality of the block readout method and the scalability of the imager are confirmed by fabrication of a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="TeX">\(4\times 4\) </tex-math></inline-formula> block and a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="TeX">\(16\times 16\) </tex-math></inline-formula> array.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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