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Record W2064168952 · doi:10.1071/zo99043

The relationships between brain regions and forelimb dexterity in marsupials (Marsupialia): a comparative test of the principle of proper mass

2000· article· en· W2064168952 on OpenAlexaff
Andrew N. Iwaniuk, John E. Nelson, Ian Q. Whishaw

Bibliographic record

VenueAustralian Journal of Zoology · 2000
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEvolution and Paleontology Studies
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsForelimbCerebrumBiologyCerebellumAnatomyBrain sizeWristCortex (anatomy)NeuroscienceCerebral cortexCentral nervous systemMagnetic resonance imagingMedicine

Abstract

fetched live from OpenAlex

A behavioural index of forelimb dexterity and comparative statistics were used to analyse the relationships between proximal (shoulder, upper and lower forelimb) and distal (wrist, forepaw, digits) forelimb dexterity and four aspects of brain morphology (overall brain, cortex, cerebellum and telencephalon sizes) in 18 species of marsupials. On the basis of the principle of proper mass, it was expected that an increase in forelimb dexterity (either proximal or distal) would be positively correlated with the size of the brain and the three brain components. Using independent contrast analysis to remove the effects of phylogeny revealed three significant correlations between: cortex size and distal dexterity, cerebellum size and proximal dexterity, and telencephalon size and distal dexterity. The relationship between cortex size and distal dexterity was subsequently corroborated by Spearman rank correlations. These results suggest that the execution of finely coordinated forelimb movements may not be dependent upon overall brain size, but may be dependent upon the size of brain components, thus supporting the principle of proper mass.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.863

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.085
GPT teacher head0.297
Teacher spread0.212 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations21
Published2000
Admission routes1
Has abstractyes

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