Climatic droplet keratopathy: an old disease in new clothes
Bibliographic record
Abstract
Climatic droplet keratopathy (CDK) is an acquired and potentially handicapping cornea degenerative disease that is highly prevalent in certain rural communities around the world. It predominantly affects males over their forties. It has many other names such as Bietti's band-shaped nodular dystrophy, Labrador keratopathy, spheroidal degeneration, chronic actinic keratopathy, oil droplet degeneration, elastoid degeneration and keratinoid corneal degeneration. CDK is characterized by the haziness and opalescence of the cornea's most anterior layers which go through three stages with increasing severity. Globular deposits of different sizes may be histopathologically observed under the corneal epithelium by means of light and electron microscopy. The coalescence and increased volume of these spherules may cause the disruption of Bowman's membrane and the elevation and thinning of the corneal epithelium. The exact aetiology and pathogenesis of CDK are unknown, but they are possibly multifactorial. The only treatment in CDK advanced cases is a corneal transplantation, which in different impoverished regions of the world is not an available option. Many years ago, the clinical and histological aspects of this disease were described in several articles. This review highlights new scientific evidence of the expanding knowledge on CDK's pathogenesis which will open the prospect for new therapeutic interventions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".