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Record W1838493152 · doi:10.1139/z11-007

Bite force and jaw biomechanics in the subterranean rodent Talas tuco-tuco (<i>Ctenomys talarum</i>) (Caviomorpha: Octodontoidea)

2011· article· en· W1838493152 on OpenAlexvenueno aff
Federico Becerra, Alejandra Isabel Echeverría, Aldo Iván Vassallo, Adrià Casinos

Bibliographic record

VenueCanadian Journal of Zoology · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEvolution and Paleontology Studies
Canadian institutionsnot available
FundersUniversidad Nacional de Mar del PlataMinisterio de Ciencia e InnovaciónConsejo Nacional de Investigaciones Científicas y Técnicas
KeywordsBiologySexual dimorphismAdductor musclesRodentAllometryBite force quotientJumpingZoologyAnatomyEcologyPhysiology

Abstract

fetched live from OpenAlex

The Talas tuco-tuco ( Ctenomys talarum Thomas, 1898) is a South American subterranean rodent that digs using both forelimbs and incisors, the latter being used when animals face hard soils and fibrous roots. In this rodent, the incisors are also used during intermale competition for mates. Bite forces were measured on wild females (n = 21) and males (n = 21) (both adult and young individuals) using a force transducer. Bite force was significantly higher in adult males than in females (32 vs. 27 N, respectively). Bite forces calculated on the physiological cross-section of jaw adductor muscles in dissected specimens were slightly higher than in vivo measurements. Regressions against body mass showed that bite force scaled with positive allometry, with slopes of 0.89 (females) and 0.99 (males). No significant differences were observed, neither in the slope nor in the y intercept of both sexes’ equations; therefore intersexual differences in bite forces observed in adults should mainly be due to size dimorphism. Considering that soil hardness of C. talarum’s typical habitat averages 100 N/cm 2 , and taking into account incisor’s cross-section, it was assessed that the pressure exerted by jaw adductor muscles at the incisors level is three times higher than that required for soil penetration.

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 score0.903
Threshold uncertainty score0.959

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)0.0010.000

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 head0.036
GPT teacher head0.200
Teacher spread0.164 · 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

Citations57
Published2011
Admission routes1
Has abstractyes

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