Structured Light in Vision Science Applications
Bibliographic record
Abstract
The dichroic macular pigment in the eye acts as a natural radial polarization filter and enables humans to directly perceive polarization-related entoptic phenomena. Linearly polarized blue light induces a subtle bowtie-like pattern known as Haidinger’s brush in the central point of vision. The clarity and shape of this perceived pattern are directly linked to the health of the macula, rendering Haidinger’s brush a potential diagnostic marker in research on early-stage age-related macular degeneration (AMD) and central field visual dysfunction. However, due to the faint nature of this signal, integrating the perception of Haidinger’s brush into modern clinical methods remains a challenge. Here we review some advances in techniques to increase the strength of the perceived signal by employing polarization coupled orbital angular momentum states. We successfully achieved the creation of stimuli with higher numbers of azimuthal fringes, enabling the perception and discrimination of Pancharatnam-Berry phases, measuring the visual angle of entoptic phenomena, retinal imaging using structured light, and the creation of radially varying entoptic stimuli. Our current studies are focusing on applying the structured light methods that we developed to subjects that suffer from ocular diseases such as AMD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 0.011 |
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".