A Comparison of the Developmental Rates of Three Visual Functions
Bibliographic record
Abstract
A comparison of the developmental rates of different visual functions can offer a clearer understanding of the visual system and reveal whether these functions are mediated by the same or different underlying neural/optical components. In the present study, 255 children (range: 2.7 to 12.4 years) were tested monocularly on grating acuity, vernier acuity, and contrast sensitivity (CS) using similar card-based tests. Grating acuity was measured using the Teller Acuity Cards II. Vernier acuity was measured using the vernier acuity cards. CS was measured at 0.75, 3.0, and 12.0 cpd using CS cards created by our laboratory. Pearson correlation coefficients were calculated to determine the relationship between each dependent measure and age. The strength of each correlation coefficients was taken as an index of developmental rate. The correlation coefficients were compared to determine whether there were significant differences in developmental rates. Vernier acuity demonstrated the most rapid developmental rate (r=-0.64), followed in order by CS at 12 cpd (r=0.58), grating acuity (r=0.55), CS at 0.75 cpd (r=0.44), and CS at 3.0 cpd (r=0.33). However, the rate of vernier acuity development was not significantly faster than that of CS at 12 cpd or grating acuity (both p>.05). Both vernier acuity and CS at 12 cpd demonstrated significantly faster developmental rates than CS at 3 and 0.75 cpd (both p< .05). The results also indicate that vernier acuity surpasses grating acuity and becomes a hyperacuity between 3 and 4 years of age. The finding that the developmental rates of vernier acuity and grating acuity did not differ was surprising as they are speculated to be mediated by different underlying components (grating acuity: retina; vernier acuity: visual cortex). Also, the faster developmental rate of CS at 12 cpd compared to 3 and 0.75 cpd may reflect the existence of different underlying spatial frequency channels. Meeting abstract presented at VSS 2017
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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 | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".