Detecting axial heterogeneity of birefringence in layered turbid media using polarized light imaging
Why this work is in the frame
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Bibliographic record
Abstract
The structural anisotropy of biological tissues can be quantified using polarized light imaging in terms of birefringence; however, birefringence varies axially in anisotropic layered tissues. This may present ambiguity in result interpretation for techniques whose birefringence results are averaged over the sampling volume. To explore this issue, we extended the polarization sensitive Monte Carlo code to model bi-layered turbid media with varying uniaxial birefringence in the two layers. Our findings demonstrate that the asymmetry degree (ASD) between the off-diagonal Mueller matrix elements of heterogeneously birefringent samples is higher than the homogenously birefringent (uniaxial) samples with the same effective retardance (magnitude and orientation). We experimentally verified the validity of ASD as a birefringence heterogeneity measure by performing polarized light measurements of bi-layered elastic and scattering polyacrylamide phantoms.
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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 | 0.001 |
| 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 it