Statistical properties of dynamic speckles from flowing Brownian scatterers in the vicinity of the image plane in optical coherence tomography
Bibliographic record
Abstract
A closed-form analytical expression is obtained for the spatio-temporal correlation function of the scattered radiation detected in fiber-based optical coherence tomography (OCT), assuming a clean optical system arrangement in the OCT sample arm. It is shown that the transverse flow component causes purely translational speckle motion with the predicted speckle velocity 2x higher than the velocity of the flowing particles as would be observed in the image plane under incoherent illumination. It is also shown that both speckle velocity and speckle radius do not depend on the position of the scattering volume relative to the focal plane, hence the derived correlation function is independent of the position of the scattering volume relative to the focal plane. Although the analytical results are obtained for a clean optical system arrangement, they can be used with high accuracy in most practical implementations of fiber based OCT. Validation experiments in control scattering phantoms with varying liquid viscosities show excellent agreement with the developed theoretical model, under both no-flow and flow conditions. Accurate viscosity determinations enabled by this methodology may have applications to non-invasive glucose measurements in medicine.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".