Coronavirus-associated epizootic catarrhal enteritis in ferrets
Bibliographic record
Abstract
OBJECTIVE: To characterize clinical signs and lesions and identify the etiologic agent associated with epizootic catarrhal enteritis in domestic ferrets. DESIGN: Cross-sectional study. ANIMALS: 119 ferrets with epizootic diarrhea of presumed viral cause and 5 control ferrets. PROCEDURE: Clinical records and biopsy or necropsy specimens of ferrets with presumed epizootic catarrhal enteritis were reviewed. Immunohistochemical staining for coronavirus antigen was performed on paraffin-embedded tissues from approximately 10% of affected ferrets to identify viral antigen and determine its distribution. Transmission electron microscopy was performed on fecal samples and sections of jejunum. Virus isolation studies as well as immunofluorescent tests for other similar viruses were performed. RESULTS: Characteristic microscopic lesions consistent with intestinal coronavirus infection (vacuolar degeneration and necrosis of villus enterocytes; villus atrophy, fusion, and blunting; and lymphocytic enteritis) were consistently detected in affected ferrets. Coronavirus particles were identified in feces and jejunal enterocytes by use of transmission electron microscopy. Immunohistochemical staining of jejunal sections revealed coronavirus antigens. Antigen staining was not detected in healthy ferrets or ferrets with other gastrointestinal tract diseases. Virus isolation was unsuccessful, and other similar viruses were not detected. CONCLUSIONS AND CLINICAL RELEVANCE: Results strongly implicate a coronavirus as the causative agent of epizootic catarrhal enteritis in ferrets. Diagnosis may be made on the basis of a combination of historical, clinical, and microscopic findings.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".