Down a Rabbit Hole: Burrowing Behaviour and Larger Home Ranges are Related to Larger Brains in Leporids
Bibliographic record
Abstract
Abstract Studies on the evolution of brain size variation usually focus on large clades encompassing broad phylogenetic groups. This risks introducing ‘noise’ in the results, often obscuring effects that might be detected in less inclusive clades. Here, we focus on a sample of endocranial volumes (endocasts) of 18 species of rabbits and hares (Lagomorpha: Leporidae), which are a discrete radiation of mammals with a suitably large range of body sizes. Using 60 individuals, we test five popular hypotheses on brain size and olfactory bulb evolution in mammals. We also address the pervasive issue of missing data, using multiple phylogenetic imputations as to conserve the full sample size for all analyses. Our analyses show that home range and burrowing behaviour are the only predictors of leporid brain size variation. Litter size, which is one of the most widely reported constraints on brain size, was unexpectedly not associated with brain size. However, a constraining effect may be masked by a strong association of litter size with temperature seasonality, warranting further study. Lastly, we show that unreasonable estimations of phylogenetic signal (Pagel’s lamba) warrant additional caution when using small sample sizes, such as ours, in comparative studies.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".