Clinical and pathological features of hair coat abnormalities in curly coated retrievers from UK and Sweden
Bibliographic record
Abstract
OBJECTIVES: To gain information on hair loss amongst curly coated retrievers by questionnaire and to define the clinical and pathological features of hair coat abnormalities in affected dogs in the United Kingdom and Sweden. MATERIALS AND METHODS: Questionnaires were completed by members of the Curly Coated Retriever Clubs. Fourteen dogs (six in the United Kingdom, eight in Sweden) were clinically examined and skin/hair samples collected for microscopy and histopathology. Blood was collected for haematological, biochemical and endocrine assays. RESULTS: Of 90 dogs surveyed, 39 had current or previous episodes of symmetrical, non-pruritic alopecia and or frizzy coat changes, usually affecting caudal thighs, axillae, dorsum and neck before 18 months of age; 23 dogs had a waxing/waning course. Examined dogs generally matched the pattern described in questionnaires. Hair shaft anomalies comprised occasional distorted anagen bulbs (10 dogs) and transverse fractures (8 dogs). Vertical histopathological sections showed infundibular hyperkeratosis (28 of 30 sections) and low-grade pigment clumping (17 of 30). Subtle telogenisation of hair follicles was unequivocally confirmed by transverse histomorphometric analyses. CLINICAL SIGNIFICANCE: The follicular dysplasia of curly coated retriever reported here is similar to that of Irish water spaniels and Chesapeake Bay retrievers but distinct from that of Portuguese water dogs. The genetic basis requires further assessment.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".