Dynamic Fusional Vergence Eye Movements in Congenital Esotropia
Bibliographic record
Abstract
PURPOSE: To evaluate whether a selected group of 9 children with history of congenital esotropia is capable of producing vergence eye responses to fusional disparity stimuli. METHODS: Nine children with history of congenital esotropia and 5 age-matched children with normal binocular vision were examined. Using a full-field target, vergence responses to base out 3 prism diopters placed in front of both eyes were recorded. RESULTS: In five patients, the initial response was a saccade generated by the dominant eye, followed by a disconjugate movement of one or both eyes. In two patients with long standing uncorrected strabismus, the responses were almost purely saccadic, while in two other patients, in whom early surgery resulted in fusional abilities, smooth vergence movements were recorded. CONCLUSION: This study adds further evidence that patients with history of congenital esotropia patients are capable of producing vergence eye movements in response to fusional disparity. The responses usually start with a saccade followed by a vergence response. The preference for initial saccadic or vergence response is correlated with sensorial tests of stereopsis and motor fusion and may be related to the size of the suppression scotoma in the deviating eye, the duration of misalignment, or both.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.000 |
| 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".