MétaCan
Menu
Back to cohort
Record W2025142506 · doi:10.1139/z01-037

Interspecific variation in sexual dimorphism in brain size in Nearctic ground squirrels (<i>Spermophilus</i> spp.)

2001· article· en· W2025142506 on OpenAlexfundvenueno aff
Andrew N. Iwaniuk

Bibliographic record

VenueCanadian Journal of Zoology · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSexual dimorphismBiologyBrain sizeInterspecific competitionZoologyGround squirrelMatingEcology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.750
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.016
GPT teacher head0.231
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations32
Published2001
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of ZoologySame topicAnimal Ecology and Behavior StudiesFrench-language works237,207