What guides lemmings movements through the snowpack?
Bibliographic record
Abstract
Abstract The presence of a snowpack, which may last up to 9 months in the Arctic, can provide insulation from the cold winter temperature for small mammals living beneath it, such as lemmings. Since lemmings have to move through the snowpack during that period, it is important to better understand how the physical properties of snow affect the way they dig tunnels. Here, we tested 1) whether lemmings systematically dig in the snowpack at the ground level where they can find their food plants, and 2) whether they choose the softest snow layer in which to dig, which is usually the depth hoar layer in the arctic snowpack. We found 33 lemming tunnels in 2017 and 2018 by digging through the snow at the sites of arctic fox attacks on lemmings. Contrary to our expectation, almost all the tunnels (32/33) were found to be higher than ground level, probably because of the presence of obstacles (i.e., melt-freeze crusts or hummocks) at the base of the snowpack. As predicted, all tunnels were dug in the soft depth hoar layer, which had a lower density than snow layers below and above it. Lemmings also showed a preference to dig their tunnels at the top of the depth hoar, just below a hard snow layer. Systematically digging their tunnels in the lowest-density snow layer, regardless of its height in the snow pack, could be a strategy for lemmings to minimize energy expenditure, which could improve their survival and chances of reproducing in winter.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.091 | 0.003 |
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; both teacher heads agree on what is shown here.
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".