Aging Effects on Vernier Hyperacuity: a Function of Oscillation Rate but not Target Contrast
Bibliographic record
Abstract
PURPOSE: Most previous studies have shown static vernier acuity for high-contrast targets to be largely unaffected by aging; those examining adult age differences on oscillatory displacement thresholds have consistently reported marked age deficits. The goals of this study were to (1) measure the age deficit on oscillatory discrimination beyond that attributable to any change in spatial discrimination by using the same target configuration for both task types and (2) determine whether an age-related change in the contrast response of the visual system contributes to age differences on static or oscillatory discrimination. METHODS: The displacement thresholds of young and old observers for a vernier task configuration were determined at two target contrast levels (0.08 and 0.64) for static and oscillating targets (2 and 6 Hz) RESULTS: No age differences were seen on static displacement thresholds at either high or low contrast. A marked age deficit that emerged when oscillation was increased was unrelated to target contrast or observer contrast sensitivity. CONCLUSIONS: Age-related declines in oscillatory discrimination beyond those attributable to spatial discrimination do not appear to be attributable to optical factors nor to a decline in the contrast response of the senescent visual system. These findings are discussed in terms of a functional decline in the magnocellular pathway, or "neural entropy," possibly due to random cell loss.
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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 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".