Clinical Comparison of High‐resolution and Standard Refractions and Prescriptions
Bibliographic record
Abstract
SIGNIFICANCE: Recently, novel refraction technology allows subjective refractions to be performed with a higher-resolution. It is unclear, however, if these benefits are noticed and appreciated by the patient during the examination and after dispensing. PURPOSE: This study investigated benefits and drawbacks of high-resolution refraction technology over standard, specifically in terms of the refraction, glasses prescription, and participant's perceptions of the technology. METHODS: Sixty progressive-addition-lens wearers (aged 35 to 70 years) and 60 single-vision wearers (18 years or older) were randomized to a high-resolution refraction (Vision-R 800; Essilor Instruments, Dallas, TX; essilorinstrumentsusa.com ) and standard refraction in a 2-week crossover dispensing design. Refractive results were converted to M, J0, and J45 and analyzed using multivariate t tests. Bayesian estimation was used to analyze differences between refraction type and age group for subjective outcomes. RESULTS: Differences in refractive error between the two refractions were small, and none differed statistically ( P > .05) or clinically (e.g., <0.25 D) in either subgroup. Visual acuities at distance and near were better than 0.00 logMAR; none of the mean differences between the refractions reached statistical or clinical (e.g., <0.10 D) significance. Participants significantly preferred the high-resolution refraction for its quickness and efficiency, improved comfort, and less stress. Bayesian analysis indicated a 76% probability that participants had higher confidence in the high-resolution refraction, 93% probability that they would seek it out for their care, and 94% probability that they would recommend an optometrist using this technology. CONCLUSIONS: Refractive and acuity endpoints were similar with the high-resolution and standard refraction. Participants, however, perceived several key benefits of the high-resolution refraction and prescription for their care, the care of their friends/family, and the practice itself.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".