Ginkgo Biloba Extract in Ophthalmic and Systemic Disease, With a Focus on Normal-Tension Glaucoma
Bibliographic record
Abstract
Glaucoma is a neurodegenerative eye disease that results in retinal ganglion cell loss and ultimately loss of vision. Elevated intraocular pressure (IOP) is the most common known risk factor for retinal ganglion cell damage and visual field loss, and the only modifiable risk factor proven to reduce the development and progression of glaucoma. This has greatly influenced our approach and assessment in terms of diagnosis and treatment. However, as many as ≥50% of patients with progressive vision loss from primary open angle glaucoma without IOP elevation (≤22 mm Hg) have been reported in the United States and Canada; 90% in Japan and 80% in Korea. Extensive research is currently underway to identify the etiology of risk factors for glaucoma other than or in addition to elevated IOP (so-called "normal-tension" glaucoma; NTG) and use this knowledge to expand available treatment options. Currently, Food and Drug Administration-approved medications for glaucoma exclusively target elevated IOP, suggesting the need for additional approaches to treatment options beyond the current scope as the definition of glaucoma changes to encompass cellular and molecular mechanisms. This review focuses on alternative medical approaches, specifically Ginkgo Biloba extract, as a potential treatment option for normal-tension glaucoma.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".