Prevalence of Chronic Ocular Diseases in a Genetic Isolate: The Norfolk Island Eye Study (NIES)
Bibliographic record
Abstract
PURPOSE: Over 40% of the permanent population of Norfolk Island possesses a unique genetic admixture dating to Pitcairn Island in the late 18(th) century, with descendents having varying degrees of combined Polynesian and European ancestry. We conducted a population-based study to determine the prevalence and causes of blindness and low vision on Norfolk Island. METHODS: All permanent residents of Norfolk Island aged ≥ 15 years were invited to participate. Participants completed a structured questionnaire/interview and underwent a comprehensive ophthalmic examination including slit-lamp biomicroscopy. RESULTS: We recruited 781 people aged ≥ 15, equal to 62% of the permanent population, 44% of whom could trace their ancestry to Pitcairn Island. No one was bilaterally blind. Prevalence of unilateral blindness (visual acuity [VA] < 6/60) in those aged ≥ 40 was 1.5%. Blindness was more common in females (P=0.049) and less common in people with Pitcairn Island ancestry (P<0.001). The most common causes of unilateral blindness were age-related macular degeneration (AMD), amblyopia, and glaucoma. Five people had low vision (Best-Corrected VA < 6/18 in better eye), with 4 (80%) due to AMD. People with Pitcairn Island ancestry had a lower prevalence of AMD (P<0.001) but a similar prevalence of glaucoma to those without Pitcairn Island ancestry. CONCLUSIONS: The prevalence of blindness and visual impairment in this isolated Australian territory is low, especially amongst those with Pitcairn Island ancestry. AMD was the most common cause of unilateral blindness and low vision. The distribution of chronic ocular diseases on Norfolk Island is similar to mainland Australian estimates.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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 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".