Variation in fur farm and wild populations of the red fox, Vulpes vulpes (Carnivora: Canidae). Part II: Craniometry
Bibliographic record
Abstract
The skulls of 165 red foxes (75 wild and 90 farm-bred individuals) collected in Poland in the years 2012–2014 were measured, analysed, and compared to further investigate the effect of ancestry and selective breeding on craniometrical variation between wild and farm red fox populations. Univariate comparisons of skull measurements (19 cranial traits), as well as four craniometric indices, revealed significant differences among vast majority of the studied measurements. Principal component analyses and two-dimensional plots showed almost complete separation of the two studied populations of the red fox, as well as clear separation of sexes between populations and within the farm population. This may suggest that the selective forces (artificial vs. natural selection) acting upon cranial morphology of the red fox vary between wild and farm populations. Furthermore, the second important factor which cannot be ignored when considering morphological differences between wild and farm foxes is the origin of compared populations (the Eurasian wild red fox population vs. the red foxes of North American origin — a founder population of farm foxes). Thus, the ancestry of the farm foxes is 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".