Equine Primary Liver Tumors: A Case Series and Review of the Literature
Bibliographic record
Abstract
Hepatoblastoma (HB) is an uncommon pediatric liver tumor in humans and horses. In humans, HB is most frequently diagnosed in fetuses, neonates, and young children, whereas hepatocellular carcinoma (HCC) affects juvenile and adult humans. Hepatoblastoma in the horse is rare, with only 9 reported cases. Affected horses ranged in age from late-term aborted fetuses to 3 years. The current study describes 3 new cases of primary liver tumors in horses and reviews findings in relation to other reports on this condition. Tumors classified as HB were identified in a male Standardbred aborted fetus and in a 4-year-old Thoroughbred filly. Hepatocellular carcinoma was diagnosed in a 15-month-old Paint filly. In the Standardbred fetus, the tumor was only present in the liver. In the Thoroughbred and Paint fillies, primary tumors were in the right liver lobe and at the hilus, respectively, and there were metastases to other lobes (HB) and mesenteric lymph nodes (HCC). Tumors were sharply demarcated from adjacent tissue, nonencapsulated, compressive, and invasive. Consisting of cords and nests, or disorganized sheets of epithelial cells, tumors had variable stromal and vascular components. The fetal tumor contained areas of smaller, less differentiated cells with a pronounced mesenchymal component interpreted to be embryonal hepatic tissue. Diagnoses were based on tumor histomorphologic features, resemblance to hepatocyte developmental stages, age of the animal, and patterns of metastasis. Tumors classified as HB were alpha-fetoprotein immunoreactive. Primary hepatic tumors in the horse are diverse in morphology and include subtypes compatible with classification criteria applied to human tumors.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".