Addison's disease due to bilateral adrenal malignancy in a dog
Bibliographic record
Abstract
A 12-year-old Rottweiler cross Labrador was presented with anorexia and weakness. Adrenal insufficiency was diagnosed with hyponatraemia, hyperkalaemia and undetectable resting and post-ACTH cortisol and aldosterone concentrations. The only abnormal diagnostic imaging result was bilateral adrenomegaly. Cytologic findings of liver, spleen and peripheral lymph nodes were normal. The dog responded initially to standard replacement therapy but relapsed shortly afterwards. The owners opted for euthanasia and allowed only removal of both adrenal glands. Microscopically, infiltrative polymorphic proliferations of densely packed tumour cells arranged as nests, intermingled with multifocal areas of necrosis and inflammatory cells were found. Silver staining revealed a few non-neoplastic adrenomedullary cells, whereas neoplastic cells did not stain. Immunohistochemistry was negative for neuron-specific enolase, vimentin, cytokeratin, synaptophysin, chromogranin A, S-100 protein, CD 56, 79 and 3. The final diagnosis was highly anaplastic bilateral adrenal neoplasia. This is the first report of bilateral adrenal malignancy presenting as clinical hypoadrenocorticism in a dog.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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; 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".