Endocranial shape variation and allometry in Euarchontoglires
Bibliographic record
Abstract
While brain size in primates and their relatives within Euarchontoglires is well-studied, less research has examined brain shape, or the allometric trajectories that underlie the relationship between size and shape. Defining these patterns is key to understanding evolutionary trends. 3D geometric morphometric analyses of endocranial shape were performed on 140 species of extant euarchontoglirans using digital cranial endocasts. Principal component analyses on Procrustes shape variables show a clear phylogenetic pattern in endocranial shape, supported by an ANOVA which identified significant differences in shape among several groups (e.g., Platyrrhini, Strepsirrhini, Scandentia, Rodentia, and Lagomorpha). ANOVAs of shape and size also indicate that allometry has a small but significant impact on endocranial shape across Euarchontoglires, with homogeneity of slopes tests finding significant differences in the scaling relationship between shape and size among these same groups. While most of these clades possess a distinct endocranial morphotype, the highly derived platyrrhines display the strongest relationship between size and shape. Rodents show the most diversity in endocranial shape, potentially attributed to their comparatively weak relationship between shape and size. These results suggest fundamental differences in how shape and size covary among Euarchontoglires, which may have facilitated the adaptive radiations that characterize members of this group.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".