Bibliographic record
Abstract
The patient, a 10-year-old female spayed Miniature Schnauzer dog, was referred to the Cornell University Hospital for Animals for hypercalcemia and a four-day history of anorexia, vomiting, lethargy, weakness, and wobbly gait. On rectal exam, a firm, non-expressible, 6 cm in diameter right anal sac mass was palpated. Initial laboratory data was suggestive of renal failure. The anal gland mass was aspirated, and cytology revealed the definitive diagnosis of apocrine gland adenocarcinoma of the anal sac. Imaging revealed evidence of local and distant cancer metastasis. Palliative treatment was elected, and pamidronate, prednisone, and fluid diuresis were used to decrease the patient?s serum calcium levels. The patient remained severely azotemic, despite aggressive fluid therapy. Serum calcium levels rapidly declined, until the patient became dangerously hypercalcemic, developed clinical signs of hypocalcemia, and required calcium supplementation. Neoplasia is the number one cause of canine hypercalcemia. This case report offers a review of calcium homeostasis, paraneoplastic hypercalcemia in the context of anal sac apocrine gland adenocarcinoma, and the medical management of calcium imbalances.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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; 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".