Towards on-chip integration of brain imaging photodetecors using standard CMOS process
Bibliographic record
Abstract
The main effects of on-chip integration on the performance and efficiency of silicon avalanche photodiode (SiAPD) and photodetector front-end is addressed in this paper based on the simulation and fabrication experiments. Two different silicon APDs are fabricated separately and also integrated with a transimpedance amplifier (TIA) front-end using standard CMOS technology. SiAPDs are designed in p+/n-well structure with guard rings realized in different shapes. The TIA front-end has been designed using distributed-gain concept combined with resistive-feedback and common-gate topology to reach low-noise and high gain-bandwidth product (GBW) characteristics. The integrated SiAPDs show higher signal-to-noise ratio (SNR), sensitivity and detection efficiency comparing to the separate SiAPDs. The integration does not show a significant effect on the gain and preserves the low power consumption. Using APDs with p-well guard-ring is preferred due to the higher observed efficiency after integration.
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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) | 0.000 | 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) | 0.001 | 0.001 |
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".