Dry Eye Disease: Consideration for Women's Health
Bibliographic record
Abstract
Dry eye disease (DED) is a multifactorial disorder of the ocular surface and tear homeostasis that can result in discomfort, pain, and visual disturbance. Untreated, DED can become chronic, progressive, and significantly affect an individual's quality of life. Women are disproportionately affected by DED, are diagnosed at a younger age, and experience more severe symptoms compared with men. DED is associated with a wide range of comorbid conditions; there is a strong association between DED and autoimmune disorders, especially those that affect women at many times the rate of men. Treatment response questionnaires indicate women respond better to a wellness model of treatment for DED than men. Furthermore, women's health care-seeking behaviors provide opportunities for general practitioners, specialists, and women's health centers to help identify women with DED or at risk for DED for referral to an eye care specialist. This review of the prevalence of DED in women, and gender and sex-specific aspects of DED, highlight a significant opportunity for action. Earlier diagnosis and treatment of this common but burdensome condition could significantly improve a woman's quality of life.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".