Diagnosis and treatment of truncal cutaneous pythiosis in a dog
Bibliographic record
Abstract
CASE DESCRIPTION: A 4-year-old spayed female Boxer was evaluated for a cutaneous mass located on the dorsum. The mass had been present for 6 weeks and was increasing in size. CLINICAL FINDINGS: A mass of approximately 10 cm in diameter was detected on the dorsum cranial to the right ilial wing. Histologic examination of a tissue sample from the mass led to the diagnosis of cutaneous pythiosis. Computed tomography of the abdomen and the mass were performed and revealed a contrast-enhancing soft tissue mass of the dorsum and enlarged intra-abdominal lymph nodes. TREATMENT AND OUTCOME: The dog underwent surgical excision of the cutaneous mass, including 5-cm skin margins and deep margins of 2 fascial planes. The mass was completely excised on the basis of results of histologic examination of surgical margins. The dog received itraconazole and terbinafine by mouth for 3 months following surgery. Recheck examination at 20 months postoperatively showed no signs of recurrence of pythiosis at the surgical site. CLINICAL RELEVANCE: Aggressive surgical excision in combination with medical treatment resulted in a favorable long-term (> 1 year) outcome in this dog. Thorough workup including diagnostic imaging and lymph node evaluation is recommended. If surgery is to be performed, skin margins of 5 cm and deep margins of 2 fascial planes are recommended.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".