Habituation of Arctic ground squirrels (Urocitellus paryii) to handling and movement during torpor to prevent artificial arousal
Bibliographic record
Abstract
Hibernation is a unique physiological adaptation characterized by periods of torpor that consist of repeated, reversible, and dramatic reductions of body temperature, metabolism, and blood flow. External and internal triggers can induce arousal from torpor in the hibernator. Studies of hibernating animals often require that animals be handled or moved prior to sampling or euthanasia but this movement can induce changes in the hibernation status of the animal. In fact, it has been demonstrated that movement of animals while they are hibernating is sufficient to induce an artificial arousal, which can detrimentally alter experimental findings obtained from animals assumed to be torpid. Therefore, we assessed a method to induce habituation of torpid hibernators to handling and movement to reduce inadvertent arousals. A platform rocker was used to mimic motion experienced during transfer of an animal and changes in respiratory rate (RR) were used to assess responsiveness of torpid Arctic ground squirrels (AGS, Urocitellus parryii). We found that movement alone did not induce a change in RR, however, exposure to handling induced an increase in RR in almost all AGS. This change in RR was markedly reduced with increased exposures, and all AGS exhibited a change in RR ≤ 1 by the end of the study. AGS habituated faster mid-season compared to early in the season, which mirrors other assessments of seasonal variation of torpor depth. However, AGS regained responsiveness when they were not exposed to daily handling. While AGS continued to undergo natural arousals during the study, occurrence of a full arousal was neither necessary for becoming habituated nor detrimental to the time required for habituation. These data suggest that even when torpid, AGS are able to undergo mechanosensory habituation, one of the simplest forms of learning, and provides a reliable way to reduce the sensitivity of torpid animals to handling.
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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 | 0.000 | 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".