Alopecia in a black Labrador retriever associated with focal sub‐follicular panniculitis and sebaceous adenitis
Bibliographic record
Abstract
A 6-year-old entire male black Labrador retriever was presented with nonpruritic multicentric, well-demarcated alopecia of 12-weeks duration. Skin biopsies from the margins of alopecic regions showed sebaceous adenitis and sub-follicular panniculitis. Biopsies from alopecic areas showed severe follicular atrophy with residual fibrous tracts, loss of sebaceous glands and lymphohistiocytic panniculitis beneath individual atrophic hair follicle groups. These features differed from previous reports of pilosebaceous diseases of dogs and appeared to extend the spectrum of inflammatory patterns in presumed immune-mediated adnexal diseases of this species. During the 12-month follow-up, there was partial hair regrowth without treatment but alopecia was permanent in the centre of larger lesions.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".