Time-resolved reflectance using short source-detector separation
Bibliographic record
Abstract
In Optical Time-Resolved Reflectance, a pair of injecting and collecting optical fibers are placed at a fixed source-detector separation from each other typically in the range of 20 to 40mm limited by the detector dynamic range. To increase the sensitivity to higher penetration depth of investigation, the source and the detector separation should be small. We first show with simulation results that short source-detector separations results in the detection of a higher number of photons coming from a greater depth. However, at these shorter distances the number of early arriving photons also increase (mainly coming from the skull and scalp regions in brain imaging) which is a constraint. To reject the early arriving photons we need a gated detector to enable detections at specified time windows. We then confirm these results in an experimental study using a simplified photon detection scheme. The dependency of the photon counts on the gate window and the source-detector separation is analyzed. We conclude that placing the laser source and the detector quite close to each other is an option to consider for the design of optodes so as to improve the image quality in various biomedical appications.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".