Endocast, brain, and bones: Correspondences and spatial relationships in squamates
Bibliographic record
Abstract
Vertebrate endocasts are widely used in the fields of paleoneurology and comparative neuroanatomy. The validity of endocranial studies is dependent upon the extent to which an endocast reflects brain morphology. Due to the variable neuroanatomical resolution of vertebrate endocasts, direct information about the brain morphology can be sometimes difficult to assess and needs to be investigated across lineages. Here, we employ X-ray computed tomography (CT), including diffusible iodine-based contrast-enhanced CT, to qualitatively compare brains and endocasts in different species of squamates. The relative position of the squamate brain within the skull, as well as the variability that may exist in such spatial relationships, was examined to help clarify the neurological regions evidence on their endocasts. Our results indicate that squamate endocasts provide variable representation of the brain, depending on species and neuroanatomical regions. The olfactory bulbs and peduncles, cerebral hemispheres, as well as the medulla oblongata represent the most easily discernable brain regions from squamate endocasts. In contrast, the position of the optic lobes, the ventral diencephalon and the pituitary may be difficult to determine depending on species. Finally, squamate endocasts provide very limited or no information about the cerebellum. The spatial relationships revealed here between the brain and the surrounding bones may help to identify each of the endocranial region. However, as one-to-one correspondences between a bone and a specific region appear limited, the exact delimitation of these regions may remain challenging according to species. This study provides a basis for further examination and interpretation of squamate endocast disparity.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".