Journal of Small Animal Practice Clinical, histopathological and genetic data of ichthyosis in the golden retriever: a prospective study.
Bibliographic record
Abstract
OBJECTIVES: We described epidemiological, clinical, histopathological and ultrastructural features of ichthyosis in the golden retriever breed in a prospective study. We also investigated the mode of transmission of this disease. MATERIALS AND METHODS: We examined 150 golden retrievers, 73 of which were affected by ichthyosis (35 males and 38 females). We carried out detailed clinical and histopathological examinations for 40 affected dogs. Transmission electron microscopy was performed for two of them. We used pedigree analysis with the Cyrillic software to determine the mode of transmission. RESULTS: Dermatological signs included a mild to moderate or severe generalised scaling with initially small to large whitish scales and progressively blackish scales. The ventral glabrous skin was hyperpigmented and rough, similar to sandpaper. Histopathological features were characterised by moderate to severe laminated or compact orthokeratotic epidermal hyperkeratosis without significant involvement of the stratum granulosum. Ultrastructural findings revealed laminated or compact keratin layers and numerous persistent corneodesmosomes within the stratum corneum. Analysis of the pedigree suggested an autosomal recessive inheritance. CONCLUSION: The histopathological and ultrastructural characteristics strongly suggest that golden retriever ichthyosis is a retention ichthyosis, caused by absence of corneodesmosomal degradation, transmitted through an autosomal recessive mode.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".