Allometric Scaling Rules of the Cerebellum in Galliform Birds
Bibliographic record
Abstract
Although the internal circuitry of the cerebellum is highly conserved across vertebrate species, the size and shape of the cerebellum varies considerably. Recent comparative studies have examined the allometric rules between cerebellar mass and number of neurons, but data are lacking on the numbers and sizes of Purkinje and granule cells or scaling of cerebellar foliation. Here, we investigate the allometric rules that govern variation in the volumes of the layers of the cerebellum, the numbers and sizes of Purkinje cells and granule cells and the degree of the cerebellar foliation across 7 species of galliform birds. We selected Galliformes because they vary greatly in body and brain sizes. Our results show that the molecular, granule and white matter layers all increase in volume at the same rate relative to total cerebellum volume. Both numbers and sizes of Purkinje cells increased with cerebellar volume, but numbers of Purkinje cells increased at a much faster rate than size. Granule cell numbers increased with cerebellar volume, but size did not. Sizes and numbers of Purkinje cells as well as numbers of granule cells were positively correlated with the degree of cerebellar foliation, but granule cell size decreased with higher degrees of foliation. The concerted changes among the volumes of cerebellar layers likely reflects the conserved neural circuitry of the cerebellum. Also, our data indicate that the scaling of cell sizes can vary markedly across neuronal populations, suggesting that evolutionary changes in cell sizes might be more complex than what is often assumed.
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 | 0.003 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".