A Binocular Approach to Treating Amblyopia: Antisuppression Therapy
Bibliographic record
Abstract
PURPOSE: We developed a binocular treatment for amblyopia based on antisuppression therapy. METHODS: A novel procedure is outlined for measuring the extent to which the fixing eye suppresses the fellow amblyopic eye. We hypothesize that suppression renders a structurally binocular system, functionally monocular. RESULTS: We demonstrate using three strabismic amblyopes that information can be combined normally between their eyes under viewing conditions where suppression is reduced. Also, we show that prolonged periods of viewing (under the artificial conditions of stimuli of different contrast in each eye) during which information from the two eyes is combined leads to a strengthening of binocular vision in such cases and eventual combination of binocular information under natural viewing conditions (stimuli of the same contrast in each eye). Concomitant improvement in monocular acuity of the amblyopic eye occurs with this reduction in suppression and strengthening of binocular fusion. Furthermore, in each of the three cases, stereoscopic function is established. CONCLUSIONS: This provides the basis for a new treatment of amblyopia, one that is purely binocular and aimed at reducing suppression as a first step.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".