The virtual brain endocast of <i>Incamys bolivianus</i>: insight from the neurosensory system into the adaptive radiation of South American rodents
Bibliographic record
Abstract
Abstract Caviomorph rodents are endemic to South America and are one of the most adaptively diverse radiations of rodents today. Although their origin and diversification have been intensively studied, questions still remain about many of the details of where, when and how the group radiated. One area of continuing debate relates to the evolution of their neurosensory system. Modern caviomorphs exhibit a rich brain shape and size diversity. So far the oldest species for which endocranial data are known is dated to the Early Miocene. Here, we describe the virtual brain endocast of the late Oligocene stem chinchillid Incamys bolivianus from Bolivia and provide new hypotheses regarding the ancestral brain of Chinchillidae and Caviomorpha more broadly. Caviomorph rodents, independent from other rodent clades, acquired an expanded neocortex and their common ancestor was probably lissencephalic or had few sulci. Incamys uniquely combines extended neocortical temporal lobes and exposed caudal colliculi, which have roles in audition and vocalization processing. We interpret this morphology as evidence for enhanced auditory acuity, vocalization processing and potentially group‐living in Incamys, which is known in modern members of the Chinchillidae family. No temporal effect was found on relative brain size in South American mammals; however, our sample is limited to available brain endocasts and as such remains small and unevenly distributed taxonomically and temporally. Incamys provides crucial insight into the evolution of the caviomorph brain and shows that we still have much to explore regarding how these small mammals achieved one the most impressive adaptive radiations of the Cenozoic.
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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 | 0.001 | 0.000 |
| 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) | 0.002 | 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".