The Barrie Jones Lecture - Eye Care for the Neglected Population: Challenges and Solutions
Bibliographic record
Abstract
Globally, pockets of 'neglected populations' do not have access to basic health-care services and carry a much greater risk of blindness and visual impairment. While large-scale public health approaches to control blindness due to vitamin A deficiency, onchocerciasis, and trachoma are successful, other causes of blindness still take a heavy toll on the population. High-quality comprehensive eye care that is equitable is the approach that needs widescale application to alleviate this inequity. L.V. Prasad Eye Institute of India developed a multi-tier pyramidal model of eye care delivery that encompasses all levels from primary to advanced tertiary (quaternary). This has demonstrated the feasibility of 'Universal Eye Health Coverage', including promotive, preventive, corrective, and rehabilitative aspects of eye care. Using human resources with competency-based training, effective and cost-effective care could be provided to many disadvantaged people.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.009 | 0.020 |
| Insufficient payload (model declined to judge) | 0.025 | 0.009 |
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".