Visual Field of High-Pass Resolution Perimetry in Normal Subjects
Bibliographic record
Abstract
PURPOSE: To investigate the properties of the visual field of high-pass resolution perimetry in normal subjects. METHODS: Four centers collected normative data for high-pass resolution perimetry. In two of the centers the subjects were stratified by age. One eye was tested per subject using high-pass resolution perimetry (Ophthimus). We tested 640 normal subjects and describe their visual field results by test location. We also analyzed the data by concentric zone, age, and by testing center. RESULTS: The individual test location averages confirmed a reduction in resolution with eccentricity. Resolution thresholds increased with age by 0.025 dB per year (P < 0.001). The mean ring size increased by about 1 dB from age 20 to 70. Among centers there were significant differences in the means and the change in threshold with age (P = 0.009). CONCLUSION: The normal visual field of high-pass resolution perimetry is characterized by an increase in threshold with eccentricity. We found significant differences among the centers that were likely due to multiple factors including differences in subject selection criteria. Whether such differences occur with other perimetric techniques is unknown.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".