Use of a Photographic Manipulation Tool to Assess Corneal Vascular Response
Bibliographic record
Abstract
PURPOSE: Corneal vasculature change in contact lens wearers has been linked to the level of hypoxia within the cornea.To assess the impact a treatment has on limbal vessels, a sensitive method of measurement and quantification is required. METHODS: A group of 21 highly myopic, hydrogel wearers, with preexisting signs of corneal hypoxia, were enrolled into a study where they wore sifilcon A penetrated hydrogel lenses (Dk/t ± 117), on a daily wear basis for 9 months. At all scheduled visits, photographs were taken of the superior, inferior, temporal, and nasal limbal regions which were then imported into Adobe Photoshop. A red-free filter was applied to enhance the contrast of the blood columns. In each quadrant, the length of the longest visible blood column was measured and the blood columns that penetrated 0.5 mm into the cornea were counted. A control group of 11 non-lens wearers was recruited. Their photographs were taken at the beginning of the study and 9 months later. An independent, masked observer assessed the photographs. RESULTS: There was a significant decrease in the maximum penetration of the blood column in all quadrants (p = 0.001) from baseline to the 9-month visit (e.g., superior: baseline 0.84 ± 0.39 mm; 9 months 0.63 ± 0.20 mm). There was also significant reduction in the number of visible blood columns longer than 0.5 mm in each quadrant (p = 0.001) from baseline to 9 months in all quadrants (e.g., superior: baseline 14.0 ± 8.2; 9 months 6.5 ± 6.0). The control group showed no change over time for the maximum blood column length (p = 0.638) or the number of columns 0.5 mm (p = 0.341). CONCLUSIONS: A group of highly myopic subjects exhibited reduction in the maximum length and number of blood columns in the cornea when ref it with a highly permeable silicone hydrogel material. The use of photography, along with Adobe Photoshop software, provides a reliable way of measuring corneal vascular responses over time.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.004 | 0.001 |
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".