The relationship between reflex eye realignment and the percept of single vision in young children
Bibliographic record
Abstract
Effective binocular vision is dependent on both motor and perceptual function. Young children undergo development of both components while interacting with their dynamic three-dimensional environment. When this development fails, eye misalignment and double vision may result. We compared the range of image disparities over which young children display reflex motor realignment of their eyes with the range over which they report a single versus double percept. In response to step changes in the disparity of a 2.2° wide stimulus, 5-year-olds generated an adult-like reflex vergence velocity tuning function peaking at 2° of disparity, with a mean latency of 210 ms. On average, they reported double vision for stimulus disparities of 3° and larger, compared to 1° in adult reports. Three-year-olds also generated reflex vergence tuning functions peaking at approximately 2° of disparity, but their percepts could not be assessed. These data suggest that, by age 5, reflex eye realignment responses and percepts driven by these brief stimuli are tightly coordinated in space and time to permit robust binocular function around the point of fixation. Importantly, the plastic neural processes maintaining this tight coordination during growth control the stability of visual information driving learning during childhood.
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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 | 0.006 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".