Hair cycle in dogs with different hair types in a tropical region of Brazil
Bibliographic record
Abstract
Hair cycle activity has been extensively studied in humans, sheep and laboratory animals, but there is a lack of information in dogs. Besides varying according to species, breed, sex and general health, hair growth is mainly affected by climatic variations. The aim of the study was to evaluate the follicle activity in three breeds of dogs with different hair types, in the city of Viçosa, Minas Gerais (latitude 20 degrees 45'S), Brazil. Twenty-one male dogs of boxer, labrador and schnauzer breeds were trichographically analysed monthly over 12 consecutive months. Hair percentage of telogen and anagen hairs at the different stages of the hair cycle in boxers and labradors was not significantly different, but both differed from the schnauzers. A significant correlation between hair follicle cycle and environmental temperature and photoperiod was noted in the boxers and labradors. In these breeds, a larger number of telogen hairs were observed during the hottest months of the year, and an increase in anagen hairs during the coldest months. The mean percentage of telogen hairs was 93, 90 and 55.3% for boxer, labrador and schnauzer, respectively.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".