Neoplasia in 125 donkeys ( <i>Equus asinus</i> )
Bibliographic record
Abstract
A diagnosis of neoplasia was noted in 125 of 357 donkeys (35%) in our review of medical records from 5 veterinary schools in the United States and Canada. Equine sarcoid was the most common tumor in our study, accounting for 72% of all tumors and 82% of cutaneous tumors. Soft-tissue sarcomas were the second most common skin tumors. All other types of neoplasia were rare. Important differences in the occurrence of neoplasia in donkeys compared to horses included the rarity or absence of squamous cell carcinoma in any organ system and gray horse melanoma. Lymphosarcoma, the most common malignant tumor in horses, appears to be very rare in donkeys. We report several tumors in donkeys including melanocytoma, peripheral nerve sheath tumor, and gastrointestinal stromal tumor. Our data demonstrate commonalities as well as differences in neoplastic diseases of donkeys and horses. Understanding differences in carcinogenesis among these 2 closely related species can inform researchers pursuing pathogenic mechanisms of equine disease and inform veterinary diagnosticians regarding tumor prevalence.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".