Virtual endocasts of fossil Sciuroidea: brain size reduction in the evolution of fossoriality
Bibliographic record
Abstract
Abstract Aplodontia rufa (mountain beaver) is the only extant member of the Aplodontidae. The fossil record indicates that this family displayed greater taxonomic and ecological diversity in the past, and that the burrowing adaptations of Aplodontia might be derived. We describe the first virtual endocasts of A. rufa and of three fossil aplodontids: Prosciurus relictus and Pros. aff. saskatchewaensis (early Oligocene), and Mesogaulus paniensis (early Miocene). Our results show that the endocasts of early aplodontid rodents are more similar to those of early arboreal squirrels than to those of the later occurring aplodontids in terms of both relative size and morphology. The endocranial features observed in sciurids and early aplodontids, missing in later aplodontids, have been associated with better vision and the development of arboreality in squirrels. Basal Aplodontidae known from postcrania have been described as generalists with some features for arboreality, which may provide a basis for these similarities. In contrast, the relatively small endocasts of the later occurring aplodontids, which lack traits related to visual specialization, may reflect their burrowing adaptations, as they would be less reliant on visual cues. When integrated with data from the most primitive fossil rodents, the Ischyromyidae, these new data suggest that early squirrels and aplodontids diverged from more terrestrial ischyromyids to become more arboreal, with relatively larger brains showing traits for improved vision. Recent Aplodontidae with fossorial adaptations returned to a more ischyromyid‐like condition in their endocranial features. These results are consistent with previous observations that changes in locomotion are reflected in the endocranial anatomy of rodents.
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 | 0.001 |
| 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".