Seasonal changes in lipids, diet, and body composition of free-ranging black-tailed prairie dogs (<i>Cynomys ludovicianus</i>)
Bibliographic record
Abstract
Black-tailed prairie dogs (Cynomys ludovicianus) enter torpor intermittently during winter in the field but do not hibernate continuously from fall to spring. Previous studies have established that hibernators rely primarily on stored lipids during winter and that the storage of n6 PUFAs in white adipose tissue (WAT) is required to maintain low body temperatures during this continuous torpor. Adult (>1 year) black-tailed prairie dogs were livetrapped in the fall, winter, spring, and summer (n = 1012). To determine whether free-ranging black-tailed prairie dogs rely heavily on stored proteins during winter, we investigated seasonal changes in body composition of the prairie dogs with dual-energy X-ray absorptiometry scans. We also examined seasonal changes in lipid composition of the WAT and diet using gasliquid chromatography to determine whether black-tailed prairie dogs lack the lipids necessary for hibernation. Seasonal changes in fat, lean, and total body mass indicate that black-tailed prairie dogs relied heavily on stored lipids during the winter and appeared to rely on proteins primarily during periods that coincided with reproductive activity. Seasonal changes in dietary and WAT lipids indicate that WAT n6 PUFAs are used during winter and stored during summer, while WAT n3 PUFAs are stored during winter and used during summer. These patterns of lipid use are different than those reported in free-ranging hibernators and may explain why black-tailed prairie dogs experience shallow and infrequent torpor bouts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".