Ovarian mixed germ cell tumor with yolk sac and teratomatous components in a dog
Bibliographic record
Abstract
Mixed germ cell tumors of the ovary have rarely been reported in veterinary species. A 3-year-old intact female Labrador Retriever dog was presented for lethargy, abdominal distention, and a midabdominal mass. An exploratory laparotomy revealed a large (23 cm in diameter) left ovarian tumor and multiple small (2-3 cm in diameter) pale tan masses on the peritoneum and abdominal surface of the diaphragm. Histological examination of the left ovary revealed a mixed germ cell tumor with a yolk sac component with rare Schiller-Duval bodies and a teratomatous component comprised primarily of neural differentiation. The abdominal metastases were solely comprised of the yolk sac component. The yolk sac component was diffusely immunopositive for cytokeratin with scattered cells reactive for α-fetoprotein and placental alkaline phosphatase. Within the teratomatous component, the neuropil was diffusely immunopositive for S100, neuron-specific enolase, and neurofilaments with a few glial fibrillary acidic protein immunopositive cells. Ovarian germ cell tumors may be pure and consist of only 1 germ cell element or may be mixed and include more than 1 germ cell element, such as teratoma and yolk sac tumor.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".