Usefulness of Subjective Refraction Based on Measuring the Far Point of Ametropia
Bibliographic record
Abstract
BackgroundIn 2009, AMD Alliance International commissioned Access Economics Pty Limited, a world-leading independent economic consulting firm, to conduct a comprehensive study on the worldwide economic and health burdens of visual impairment.Specialists in model-based health forecasting and analysis, Access Economics has previously estimated the burden of vision loss for Australia, Canada, Japan, the United Kingdom, and the United States.This is the first study to report the burden of visual impairment for all world regions.Using regional prevalence data, the numbers of people in each World Health Organisation (WHO) subregion having visual impairment are projected for the years 2010 to 2020, and include:• People with mild visual impairment (6/18 < visual acuity ≤ 6/12)• People with moderate visual impairment (6/60 < visual acuity ≤ 6/18)• People who are blind (visual acuity < 6/60).The analysis accounts for regional demographic trends and the distribution of visual impairment by eye condition, including age-related macular degeneration (AMD), diabetic retinopathy, cataract, uncorrected refractive error and other causes.The study includes actual cost data where available and draws on previous research into national expenditures on visual impairment.Findings are extrapolated to all regions using relative health care prices and key health and economic indicators.The findings of this report are the most comprehensive data now available on the global burden of visual impairment.The breadth of results covers the direct health care system costs, the value of lost productivity (due to disability and premature death) and informal caregiver time, and the deadweight welfare losses in raising tax revenue to fund health care.All costs are reported in 2008 US dollars.Global and regional disability-adjusted life year (DALY) burdens are also reported.This document provides a summary of the full report, The Global Economic Cost of Visual Impairment, which will be released in 2010. About AMD Alliance International:AMD Alliance International strives to bring knowledge, help and hope to individuals and families around the world affected by AMD.Their mission is to bring knowledge, hope, and help to individuals and families around the world affected by AMD, and is accomplished through:• Generating awareness and understanding of AMD;• Promoting the importance of education, early detection, knowledge of treatment and rehabilitation;
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".