Smart squirrels use a mortise-tenon structure to fix nuts on understory twigs
Bibliographic record
Abstract
Abstract Squirrels of temperate zones commonly store nuts or seeds under leaf litter, in hollow logs or even in holes in the ground; however, in humid rainforests, it is an evolutionary challenge for squirrels to hang elliptical or oblate nuts securely on trees to minimize germination or fungal infection. Here, we report a unique behaviour used by two species of small flying squirrels ( Hylopetes phayrei electilis (G. M. Allen, 1925) and Hylopetes alboniger (Hodgson, 1870)) to cache nuts on Hainan Island. Squirrels intentionally carved grooves encircling ellipsoid nuts or distributed on the bottom of oblate nuts and used these grooves to fix nuts tightly between small twigs 0.1-0.6 cm in diameter and connected at angles of 25-40°. The resulting structures were similar to the mortise-tenon joint of ancient Chinese architecture. Cache sites were on small plants located 10-25 m away from the closest potentially nut-producing tree, a behaviour that likely deters discovery and consumption of the nuts by other animals. Their ability to shape individual nuts to store them more securely suggests it is a smart behavior, which is likely formed by the adaption to life in humid tropical rainforests to guarantee food supply and impacts the distribution of tree species.
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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".