Direct-Conversion CMOS X-Ray Imager With <inline-formula> <tex-math notation="LaTeX">$5.6 ~\mu \text{m} \times 6.25~\mu \text{m}$ </tex-math></inline-formula> Pixels
Bibliographic record
Abstract
We report a monolithic direct-conversion X-ray imager capable of detecting diagnostic level X-rays. The imager is constructed by combining a custom 32×32 CMOS four-transistor active pixel sensor (4T APS) array with an amorphous selenium photoconductive layer deposited on top of the array via a post processing step. A 4T APS with an explicit per-pixel integration capacitor is employed to increase the pixel dynamic range. Under dark conditions, an input-referred electronic noise of <;90 electrons (rms) is estimated based on measured noise data for a 40-ms integration time. The very first X-ray images of copper and stainless-steel objects are included to demonstrate the performance of what is, to the best of our knowledge, a direct-conversion X-ray imager with the smallest pixel pitch reported to date.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".