An analysis of canine hair re‐growth after clipping for a surgical procedure
Why this work is in the frame
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Bibliographic record
Abstract
Hair growth and replacement have been studied extensively in humans, sheep and laboratory rodents, but in dogs and other mammalian species few studies have been published. The objectives of this study were: (1) to determine the time required for the hair to re-grow in dogs after clipping for a surgical procedure; (2) to define whether the season of the year influenced the period of time required for re-growth and; (3) to determine if season might influence the telogen: anagen ratio. Eleven Labrador retrievers were recruited during spring, 10 during summer, six during autumn and 10 during winter. Hairs re-grew to their preclipped length in 14.6 weeks, 14.5 weeks, 13.6 weeks and 15.4 weeks when shaved in the spring, summer, autumn and winter, respectively. The differences in these values were not significant suggesting that season has no effect on the rate of hair re-growth in Labrador retrievers housed indoors (P = 0.12). The mean values for the telogen: anagen ratio in each season were: 5.2 (spring), 6.1 (summer), 9.5 (autumn), and 5.3 (winter). The differences in these values also were not significant (P = 0.89). The percentage of hairs in telogen was over 80% in all four seasons.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it