Psychophysical and image-based characterization of macular pigment using structured light
Bibliographic record
Abstract
Macular pigment is thought to underlie entoptic percepts that enable human discrimination of polarized light. Therefore, polarization sensitivity may be a useful probe of macular pigment density and the risk of future macular disease. Structured light beams formed through the spin coupled orbital angular momentum states exhibit spatially dependent polarization and are therefore ideally suited to quantify human polarization sensitivity. When fixating at the center of these beams, a polarization-defined entoptic percept resembling radial spokes is observed. Using such structured light, we investigated whether we could characterize the portion of retina sensitive to polarization in healthy observers and observers with subclinical macular degeneration. In Experiment 1, the beam was presented to 23 healthy participants for 500ms per trial, rotating clockwise or counterclockwise. Participants indicated the direction of rotation. A circular mask with a varying radius was placed at fixation, thus the task was performed at varying eccentricities. The radius of the mask was controlled by a 2-up, 1-down thresholding staircase to estimate the size of the mask eliciting 71% accuracy. In addition, a fundus image using structured light was taken alongside a standard fundus image to register the psychophysical threshold to retinal landmarks, allowing the threshold to be expressed in visual angle units. In Experiment 2, normal participants and participants with subclinical macular degeneration performed a similar task using multiple mask shapes to characterize polarization sensitivity more fully. In healthy eyes, the mask size threshold ranged between 1° and 9° (mean = 4.6° ± 0.6°). In eyes exhibiting subclinical macular degeneration, a full-field mask with a ring of visible structured light elicited the best and most reliable performance, consistent with a selective pigment deficit in the central macula. Overall, our results indicate that structured light may be a useful tool for probing human macular pigment via polarization sensitivity.
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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 | 0.002 |
| 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 | 0.000 |
| 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".