Phenotype of macular corneal dystrophy in Labrador Retrievers: A multicenter study
Bibliographic record
Abstract
OBJECTIVE: To describe the phenotype of canine macular corneal dystrophy (MCD) including the clinical presentation, multimodal ocular imaging, histopathology, and ultrastructural analysis in ten Labrador Retrievers. PROCEDURE: Multicentered data collection. RESULTS: Labrador Retrievers affected by MCD were presented between the age of 4.5 and 6 years of age with a history of cloudy eyes and/or visual impairment. Findings on ophthalmic examination included a diffuse haze of the corneal stroma and multiple, well-demarcated, off-white to yellow-brown, punctate corneal opacities heterogeneous in size. Corneal vascularization developed in most dogs as the disease progressed. Disease progression was associated with increased density of the corneal haze as well as increased number and size of the focal opacities and dogs developed significant visual impairment. Spectral domain-optical coherence tomography revealed multifocal hyper-reflective regions within the stroma. In vivo confocal microscopy revealed marked alterations in reflectivity throughout the entire stroma. Normal keratocytes could not be identified in affected areas. Histopathology showed stromal collagen fibers separated by acidophilic granular material on hematoxylin and eosin stain. The material stained with periodic acid-Schiff and colloidal iron stain but not with Masson trichrome stain, confirming the accumulation of glycosaminoglycans. On electron microscopic ultrastructural examination, keratocytes presented with vacuolated rough endoplasmic reticulum and multiple electron dense cytoplasmic inclusions. In areas keratocytes appeared ruptured, with cell organelles and proteinaceous material grouped together between collagen fibers. CONCLUSION: MCD in Labrador Retrievers has similarities with the human counterpart of the condition and is an important differential diagnosis in dogs with corneal disease.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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".