Diversity of selected features of integumentary system in mink
Bibliographic record
Abstract
Domestication by humans was aimed to modify the morphological, physiological, developmental and mental traits of the wild animals so as to obtain desirable characteristics. As a result of long-term intensive farming, the productive traits of farmed mink differ considerably from those of feral mink. Clear differences are observed in reproductive traits, and animals are improved mainly for hair coat quality, coat colour, body size and temperament. The wild American mink, a non-indigenous species that took over the European mink’s ecological niche, is found in Poland. The aim of the study was to determine differences in the integumentary system of mink depending on the animals’ place of origin and habitat. The biological material was represented by skins of feral mink caught in Canada and Poland following the winter period and skins of farmed Polish mink obtained after winter fur priming. Physical parameters of all raw skins were measured, the degree of skin damage was evaluated, and the histological examination of the skins was performed during the study because hair coat is associated developmentally and biologically with cutaneous tissue. A total of 150 skins were analysed. In relation to Canadian skins, Polish skins were 22% heavier, 15% longer and had 31% greater area, while the skins of farmed mink were 130% heavier, 52% longer and had 88% greater area.
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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 | 0.001 |
| 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) | 0.002 | 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".