Interspecific variation in sexual dimorphism in brain size in Nearctic ground squirrels (<i>Spermophilus</i> spp.)
Bibliographic record
Abstract
A possible relationship between sexual dimorphism in brain size and mating system was investigated in five ground squirrel species: Spermophilus lateralis, S. tridecemlineatus, S. richardsonii, S. columbianus, and S. parryii. Relative brain size was measured by determining the endocranial volume of 247 ground squirrel skulls and regressing these values against two measurements of body size: mass and length. Analyses of covariation in the brain size / body size relationship within the five species revealed that sexual brain-size dimorphism occurs in three of the five species: S. lateralis, S. richardsonii, and S. tridecemlineatus. Application of a reduced major axis regression model indicated, however, that only S. lateralis and S. richardsonii exhibit significant sexual brain-size dimorphism. These findings suggest that the degree of sexual brain-size dimorphism is not directly correlated with variation in mating systems. Spatial abilities may play a role in the evolution of sexual brain-size dimorphism in ground squirrels, but the spatial requirements of mating systems appear to be insufficient. The possibility of sex differences in cognition, resource competition, and other variables as contributory factors to the evolution of sexual brain-size dimorphism is offered, but detailed knowledge of sex differences in the behaviour of ground squirrels is required to provide a definitive answer.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".