Case Report: Ocular Neuromyotonia
Bibliographic record
Abstract
Orthoptists and Ophthalmologists are keenly aware of the importance of stable strabismus measurements prior to extraocular muscle surgery. Disease entities such as myasthenia gravis are frequently debated in case of unstable measurements. It is important to include ocular neuromyotonia (ONM) in the differential diagnosis of variable strabismus, particularly with a history of cranial radiotherapy and to ascertain if this diagnosis is applicable preoperatively as many of these cases respond to medical rather than surgical treatment. Our experience with ONM will be described in a case report involving a 48-year-old esotropic female who had radiation therapy for a cancerous lesion of the parotid gland 15 years previously. Her initial clinical appearance was of a large esotropia with apparent right VIth nerve paresis, eventually it was noted that an exotropia could be elicited after sustained right gaze. The exotropia lasted 15–30 seconds and is believed to be due to ONM of the right lateral rectus. This ONM, secondary to radiation/compression of the right VIth nerve, resolved with appropriate Dilantin® levels. A small persistent esotropia was amenable to prismatic correction with no strabismus surgery required.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.010 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".