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Record W2768832826 · doi:10.5206/wurjhns.2017-18.4

Evolutionary GEM: The Evolution of the Primate Prehensile Tail

2017· article· en· W2768832826 on OpenAlexaffvenue
Emily Xu, Patricia M. Gray

Bibliographic record

VenueWestern Undergraduate Research Journal Health and Natural Sciences · 2017
Typearticle
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsWestern University
Fundersnot available
KeywordsPrehensile tailArboreal locomotionBipedalismAnatomyPrimateBiologyEcomorphologyEvolutionary biologyNeuroscienceEcology

Abstract

fetched live from OpenAlex

The evolution of the prehensile tail illustrates the impact habitat can have on structural traits. Prehensile primates are able to support their entire body weight using only their tail, which opens up new feeding opportunities in their arboreal environments. This trait evolved separately in two families of New World monkeys. A transitional behaviour in its proposed evolutionary mechanism is tail-assisted hind limb suspension during locomotion in these dense forests. The evolution of more robust vertebrae, shorter distal vertebrae, a greater number of zygapophyseal joints, as well as larger and more convex articular surfaces, result in a stronger and more flexible tail. Prehensile tails have more expanded muscle attachments that can bear greater loading forces. A naked tactile pad that improves grip is present only in atelids. These differences in bone and muscle morphology make the prehensile tail more sturdy and dexterous, allowing prehensile primates to use their tails for an alternative function.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.111
GPT teacher head0.468
Teacher spread0.357 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2017
Admission routes2
Has abstractyes

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