Pancreatitis and Systemic Coronavirus Infection in a Ferret (<i>Mustela putorius furo</i>)
Bibliographic record
Abstract
A 1-y-old spayed female ferret (Mustela putorius furo) was referred for additional diagnostic evaluation after physical examination by the referring veterinarian revealed a cranial abdominal mass. The ferret had a 2-wk history of inappetence, weight loss, and lethargy. On presentation, the ferret was thin, and an approximately 3-cm mass was palpable in the cranial abdomen. No other abnormalities were noted. Abdominal ultrasonography confirmed the presence of a soft-tissue structure, with a moderate blood supply and mesenteric lymphadenopathy. Fine-needle aspirates of the mass were nondiagnostic. Exploratory laparotomy revealed multiple nodules and thickened tissues throughout the mesentery, a thickened and nodular pancreas, and a small amount of free abdominal fluid. Histopathology of mesenteric, lymphatic, and pancreatic biopsies revealed suppurative pancreatitis and necrotizing and pyogranulomatous mesenteric steatitis. Positive immunohistochemistry for feline coronavirus confirmed a diagnosis of ferret systemic coronavirus disease (FSCD). The ferret was treated medically with oral prednisolone, improved dramatically, and was still doing well 22 mo after diagnosis. Although FSCD has been reported extensively, this case is noteworthy for the presence of suppurative pancreatitis and the positive long-term outcome after corticosteroid therapy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 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".