Variation in the strength of allometry drives rates of evolution in primate brain shape - Supplementary Material
Bibliographic record
Abstract
Large brains are a defining feature of primates, as is a clear allometric trend between body mass and brain size. However, important questions on the macroevolution of brain shape in primates remain unanswered. Here we address two: (i), does the relationship between the brain size and its shape follow allometric trends and (ii), is this relationship consistent over evolutionary time? We employ three-dimensional geometric morphometrics and phylogenetic comparative methods to answer these questions, based on a large sample representing 151 species and most primate families. We found two distinct trends regarding the relationship between brain shape and brain size. Hominoidea and Cercopithecinae showed significant evolutionary allometry, whereas no allometric trends were discernible for Strepsirrhini, Colobinae or Platyrrhini. Furthermore,we found that in the taxa characterized by significant allometry, brain shape evolution accelerated, whereas for taxa in which such allometrywas absent, the evolution of brain shape decelerated.We conclude that although primates in general are typically described as largebrained, strong allometric effects on brain shape are largely confined to the order’s representatives that display more complex behavioural repertoires.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.077 | 0.055 |
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".