Optical Strategy Utilizing Contrast Modulation to Slow Myopia
Bibliographic record
Abstract
A new method to slow myopia progression utilises Diffusion Optics Technology™ (DOT) spectacle lenses. The proposed mechanism of action for the DOT lenses is to modulate contrast across the photoreceptor cells, leading to an altered activity of the ON and OFF pathways and slowing the progression of axial elongation. This approach is different to the current optical approaches that utilise optical defocus to reduce hyperopic defocus at the peripheral retina while central vision is fully corrected to slow myopia. Initial clinical studies with the DOT lenses have demonstrated promising results with a reduction in progression of myopia. This overview summarises the current knowledge on myopia risk factors, the evidence for involvement of contrast signalling pathways in refractive error development, and the theories and mechanisms behind DOT lens technology. It also considers the role for contrast and the paradoxical observations given the established paradigm of form deprivation in animal models.
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How this classification was reachedexpand
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 | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".