Morphological changes to black-footed ferrets (<i>Mustela nigripes</i>) resulting from captivity
Bibliographic record
Abstract
Captive breeding of endangered species carries risks associated with small population size and domestication. The black-footed ferret (Mustela nigripes) was among the first endangered species bred in captivity. We documented morphological changes to the species after >10 years of captive breeding. We measured 9 dental or cranial traits on 109 skulls; 85 specimens were collected prior to captivity and 24 specimens were of captive-born animals. Skulls of captive animals were 56% smaller than skulls from precaptive animals and were 310% smaller than skulls of animals collected near the founding population, suggesting that changes occurred in captivity rather than from sample bias in the founders of the captive population. Skull size did not correlate with inbreeding coefficients of captive animals, eliminating the possibility that black-footed ferrets were smaller because of the effects of inbreeding depression or overdominance. Although reintroduced animals were smaller than historical animals, we recommended no alterations to the current management because intentional selection for body size might further reduce genetic variation in a genetically impoverished species. We hypothesize that reintroduced individuals will return to historical body sizes rapidly, owing either to release of environmental stresses or to natural selection for larger size.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".