Modeling and Characterizing Optical CMOS Sensors for Biomedical Low-Intensity Light Detection
Bibliographic record
Abstract
In this work several photo-sensors include silicon PIN photodiode and avalanche photodiodes (SiAPDs) are addressed to develop a miniaturized near-infrared photo-sensor with high-sensitivity, low-power and low-noise characteristics using CMOS technology dedicated to biomedical imaging applications. These devices have been characterized and compared using different device simulators include COMSOL, TCAD, MATLAB, Crosslight-APSYS and Silvaco. The impact of simulation and reliability of the simulation results are evaluated by considering the measurement results. The sources of observed discrepancies between simulated and measured characteristics are discussed. Then a reliable technique to use device simulators and photo-sensor modeling results, is proposed based on our previous design, simulation and fabrication experiences. A new equivalent circuit model for SiAPD is also developed to be applied in circuit level simulations.
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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 | 0.000 | 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 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".