Review and analysis of grading scales for ocular surface staining
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Vital dye staining has been used for over a century to assess the severity of ocular surface disease. However, despite common usage, a universally accepted "gold standard" grading scale does not exist for corneal and conjunctival staining, which can impact the ability to diagnose and monitor ocular surface conditions such as dry eye. The Food and Drug Administration (FDA) and other international regulatory agencies rely on ocular surface staining as a primary endpoint for new drug approvals, so that absence of a "gold standard" scale may affect approval of new drug treatments. To begin to address this problem, we review existing, published grading scales in an integrated fashion, highlighting their differences and similarities to emphasize common themes and the methods and elements that are important in creating a standardized scale. Our goal is to aid the field in moving towards an accepted standardized grading scale for ocular surface staining that can be applied in clinic and research settings for a variety of ocular conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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 it