A “down under” lesion on the muzzle of a dog
Bibliographic record
Abstract
A 10-year-old, castrated, male Labrador Retriever was presented to a local veterinary practice for investigation of a firm, deeply pigmented, alopecic, subcutaneous mass (8 mm in diameter) on the left side of the muzzle. A fine-needle aspirate of the mass was submitted for cytologic evaluation to the University of Florida. Microscopically, the preparation contained a predominant population of histiocytes that contained variable numbers of intracytoplasmic, negative-staining, filamentous structures consistent with Mycobacterium sp. A presumptive diagnosis of canine leproid granuloma syndrome was based on the cytologic findings and location of the lesion. Acid-fast staining revealed bright pink, acid-fast organisms within the histiocytic cells, supporting the diagnosis. The bacteria were not detected in histopathologic sections or by a polymerase chain reaction (PCR) test 1 week later, however, possibly because of spontaneous remission. Canine leproid granuloma syndrome is a common disease in Australia, but is uncommon in dogs in North America. It is caused by a novel, unnamed Mycobacterium species and usually affects the skin and subcutaneous tissues of the head and ears. A diagnosis usually can be made in Wright's-Giemsa and acid-fast-stained cytologic specimens; however, definitive diagnosis requires PCR testing at a specialized laboratory.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 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 | 0.002 |
| 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".