Variation in fur farm and wild populations of the red fox, <i>Vulpes vulpes</i> (Carnivora: Canidae) — Part I: Morphometry
Bibliographic record
Abstract
This paper demonstrates the influence of artificial selection on morphometric traits in the red fox [Vulpes vulpes (Linnaeus, 1758)]. Measurements and two proportion coefficients were analysed in 132 wild and 199 farm red foxes. The two groups differed significantly (P ≤ 0.05) on all but one of the measurements. Eight out of 11 measurements were significantly greater in the farm fox population, while only tail length, ear height, and length of the right hind limb were greater in the population of wild foxes. The opposite trend was observed when analysing variation in the measurements — the farm foxes were characterized by a greater variability only in the case of body weight, body length, and breadth of chest. When analysing the sexual dimorphism index in different sex and population groups, in almost all analysed traits, the greatest differences occurred between farm males and wild females. All of the traits examined in this study are important for survival of wild foxes. However, because importance of some traits was reduced during domestication and selective breeding (farm foxes do not have to fight for survival), the genetic relationship between them may have weakened. Other possible causes of morphological differences between the studied groups of red foxes are discussed as well.
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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 | 0.000 | 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) | 0.001 | 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".