Bilateral retinoschisis in a dog: A veterinary clinical application for optical coherence tomography
Bibliographic record
Abstract
A 11-year-old neutered male Labrador retriever-cross dog was presented to the University of Missouri-Columbia Veterinary Ophthalmology Service for subtle visual deficits. Indirect ophthalmoscopy revealed a smooth, bullous elevation in the superior-temporal retina OU. Optical coherence tomography (OCT) performed OU showed inner retinal separation consistent with retinoschisis. Electroretinography (ERG) revealed markedly reduced b-wave amplitudes in the more severely affected eye (OD) compared with the less severely affected eye (OS). The most notable reductions were in the rod response and 30-Hz flicker b-waves OD which were approximately 50% of the corresponding amplitudes OS. Implicit times, particularly the a-wave implicit times, were noticeably longer OD compared with OS. Lesions remained unchanged over 4 months at which time the dog was humanely euthanized for reasons unrelated to the ocular disease. Significant light microscopic ocular findings were bilateral superior temporal peripheral retinoschisis. The separation of the retinal tissue was similar between eyes and effectively divided the outer plexiform layer. In addition, thinning of the surrounding retinal layers was present. To the authors' knowledge, this is the first case of canine retinoschisis diagnosed with OCT, evaluated with electroretinography, and confirmed with light microscopic examination. History, clinical, and diagnostic findings, with the absence of disease progression over time, are analogous with cases of acquired senile retinoschisis in humans.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".