Eye-related neoplasms in dogs: A retrospective study
Bibliographic record
Abstract
Background: Eye-related neoplasms in dogs have a significant impact on visual ability, comfort, and longevity. Therapeutic alternatives and prognosis vary according to type of neoplasm and its anatomical location. Objective: To describe the frequency and distribution of eye-related neoplasms affecting dogs in Aburrá valley (Antioquia province, Colombia). Methods: A retrospective collection of eye-related neoplasms in dogs, diagnosed at the Animal Pathology Laboratory of Universidad de Antioquia (Colombia), was conducted. Data spanning from years 2005 to 2017 were used. Records included age, sex, breed, neoplasm type and location, and cellular origin of neoplasm. A total of 250 eye-related-neoplasm reports affecting 246 dogs were analyzed -one report per animal, with the exception of four animals with both eyes simultaneously affected by the same type of neoplasm. Results: Animals between 8 and 11 years of age were more frequently affected by eye-related neoplasms (43.9%). Labrador retriever (19.1%), mixed-breed dogs (13.4%), and Poodle (12.2%) were the most frequently affected breeds. Neoplasms affected the eyelid in 76.8% of cases. Meibomian gland adenoma was the most frequent neoplasm (22.8%), followed by Meibomian gland epithelioma (20.0%), squamous cell carcinoma (8.8%), and melanocytoma (7.2%). The cellular origin of neoplasms [i]was epithelial in 73.6% of the cases. Conclusion: Meibomian gland adenoma was the most common eye-related neoplasm. To our knowledge, this is the first retrospective report aimed to eye-related neoplasms in dogs published in Colombia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".