Prevalence of pre-iridal monocellular and fibrovascular membranes in canine globes affected with congenital glaucoma associated with anterior segment dysgenesis, primary glaucoma associated with goniodysgenesis, and secondary glaucoma
Bibliographic record
Abstract
Objectives: The objectives of this study were to (i) evaluate the prevalence of pre-iridal monocellular and fibrovascular membranes in canine globes affected with congenital glaucoma associated with anterior segment dysgenesis (ASD), primary glaucoma associated with goniodysgenesis (GD), and secondary glaucoma, and (ii) examine the associations between monocellular and fibrovascular membranes by breed, gender, age and histopathologic ocular changes on light microscopic examination. Methods: Records of dogs who had eyes enucleated due to blindness and uncontrolled glaucoma were reviewed. Glaucoma was categorized clinically and histologically into three groups: congenital/ASD, primary/GD, and secondary glaucoma. The presence or absence and type of pre-iridal membrane (monocellular or fibrovascular) and other intraocular histologic findings were reviewed and compared statistically for each group. Results: In total, 108 canine globes (101 dogs) were included. Pre-iridal monocellular membranes were identified with light microscopy in 10 out of 19 congenital/ASD, 29 out of 40 primary, and 23 out of 49 secondary glaucoma globes. Fibrovascular membranes were observed in 3 out of 19 congenital/ASD, 9 out of 40 in primary, and 24 out of 49 secondary glaucoma globes. There were no associations between the type of membrane and breed, gender, or age. Peripheral anterior synechiae were more common in globes with fibrovascular membranes, and uveal atrophy was more common in globes with monocellular membranes. Conclusion: Pre-iridal monocellular membranes are common in all types of canine glaucoma. They are identified with light microscopy most easily in cases of primary glaucoma, and they are masked by pre-iridal fibrovascular membranes in other forms of glaucoma.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".