Polarized light propagation in multiply scattering media exhibiting both linear birefringence and optical activity: Monte Carlo model and experimental methodology
Bibliographic record
Abstract
A Monte Carlo model for polarized light propagation in birefringent, optically active, multiply scattering media is developed in an effort to accurately represent the propagation of polarized light in biological tissue. The model employs the Jones N-matrix formalism to combine both linear birefringence and optical activity into a single effect that can be applied to photons as they propagate between scattering events. Polyacrylamide phantoms with strain-induced birefringence, sucrose-induced optical activity, and polystyrene microspheres as scattering particles are used for experimental validation. Measurements are made using a Stokes polarimeter that detects scattered light in different geometries, and compared to the results of Monte Carlo simulations run with similar parameters. The results show close agreement between the experimental measurements and Monte Carlo calculations for phantoms exhibiting turbidity and birefringence, as well as for phantoms exhibiting turbidity, birefringence, and optical activity. Other scattering-independent polarization properties can be incorporated into the developed Jones N-matrix formalism, enabling quantification of the polarization effects via an accurate polarization-sensitive Monte Carlo model.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".