Lessons about visual rehabilitation from children treated for cataracts
Bibliographic record
Abstract
Studies of children treated for cataract indicate that there are different sensitive periods for different aspects of vision. For example, visual deprivation beginning at 6 months of age prevents the development of normal acuity or peripheral light sensitivity, but has no effect on sensitivity to the global direction of motion, which is affected adversely only by visual deprivation beginning near birth. Our results also indicate that the deleterious effects of visual deprivation are sometimes worse if there was not only deprivation, but also uneven competition between the eyes—because the deprivation was monocular and there was little patching of the non-deprived eye. However the adverse effects of uneven competition are not seen at all points during development or for all aspects of vision. Together, the results are consistent with theories that visual input can affect later development by (a) preventing deterioration of existing neural structures; (b) reserving neural networks (via Hebbian competition) for later refinement; (c) allowing a developmental trajectory to start from an optimal state; (d) allowing recovery from earlier deprivation via the recruiting of alternative pathways; and/or (e) allowing the refinement of previously established structures. Our results indicate that there are timing constraints on each of these mechanims that are manifested as variations in sensitive periods. The implications for visual rehabilitation will be discussed.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".