Severe Bilateral Sialadenitis of the Mandibular and Parotid Salivary Glands with Severe Panniculitis in a 2-Year-old Standard Poodle
Bibliographic record
Abstract
A 2-year-old male neutered Standard Poodle weighing 17.9 kg was presented to their primary care veterinarian for enlarged bilateral submandibular swellings following an interdog altercation sustained in the previous weeks. Cytology performed following fine-needle aspirates of the regions of swelling was inconclusive, and the patient was treated empirically with Clavaseptin. Despite treatment, the submandibular swellings continued to enlarge, and right-sided intermittent epistaxis was reported. On biochemical profile, there was mild hypercalcemia and mild hyperglobulinemia. The computed tomography (CT) findings were indicative of severe multifocal sialadenitis with severe regional cellulitis and inflammatory lymphadenopathy. Histopathology and cytology results described mixed inflammation of the salivary gland. Methenamine silver staining and Fite's acid-fast staining were negative. Aerobic and anaerobic cultures were negative. Targeted, next-generation DNA sequencing detected no known fungi or bacterial pathogens. These findings were consistent with the diagnosis of severe bilateral mandibular sialadenitis, panniculitis, and lymphadenopathy. The patient was prescribed enrofloxacin, clindamycin, phenobarbital, and prednisolone for 1 month. One week after initiating treatment, the patient had a significant reduction in size of the salivary glands. CT imaging was helpful in the diagnosis of this patient and allowed the clinician to identify which submandibular anatomical structures were abnormal, guiding subsequent diagnostic decisions to provide medical management to resolve the condition.
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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) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".