Sparing of coarse stereopsis in stereodeficient children with a history of amblyopia
Bibliographic record
Abstract
Stereoscopic depth perception may be obtained from small retinal disparities that can be fused for single vision (fine stereopsis), but reliable depth information is also obtained from larger disparities that produce double vision (coarse stereopsis). Here we assess the possibility that the early development of coarse stereopsis makes it resilient to the factors that cause amblyopia by comparing performance in children with a history of strabismic, anisometropic, or aniso-strabismic amblyopia and age-matched controls (5-12 years). The task was to indicate whether a cartoon character was nearer or farther away than a zero-disparity reference frame. Test disparities were grouped into fine and coarse ranges based on preliminary assessment of diplopia thresholds. In the fine range, accuracy increased with disparity for both groups, but children in the amblyopia group performed significantly worse than children in the control group, particularly when their amblyopia was associated with strabismus. In the coarse range, accuracy was constant across all disparities for both groups although performance appeared to be poorer in the aniso-strabismic group. These results suggest that, under some conditions, stereopsis for large disparities may be spared when stereopsis for small disparities is disrupted by early visual deprivation. This undetected residual binocular function has important clinical implications given recent efforts to improve amblyopia treatment outcomes by employing binocular treatment protocols.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".