Polarization properties of retinal blood vessel walls measured with polarization sensitive optical coherence tomography
Bibliographic record
Abstract
. Measurements were obtained near the optic nerve head of three healthy human subjects. The double pass phase retardation per unit depth (DPPR/UD), which is proportional to the birefringence, is higher in artery walls, presumably because of the presence of muscle tissue. Measurements in surrounding retinal nerve fiber layer tissue yielded lower DPPR/UD values, suggesting that the retinal vessel wall tissue near the optic nerve is not covered by retinal nerve fiber layer tissue (0.43°/µm vs. 0.77°/µm, respectively). Measurements were obtained from multiple artery-vein pairs, to quantify the different polarization properties. Measurements were taken along a section of the vessel wall, with changes in DPPR/UD up to 15%, while the vessel wall thickness remained relatively constant. A stationary scan pattern was applied to determine the influence of involuntary eye motion on the measurement, which was significant. Measurements were also analyzed by two examiners, with high inter-observer agreement. The measurement repeatability was determined with measurements that were acquired during multiple visits. An improvement in accuracy can be achieved with an ultra-broad-bandwidth PS-OCT system since it will provide more data points in-depth, which reduces the influence of discretization and helps to facilitate better fitting of the birefringence data.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".