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Record W3083741541 · doi:10.1016/j.jhevol.2020.102865

Biomechanics of the mandible of Macaca mulatta during the power stroke of mastication: Loading, deformation, and strain regimes and the impact of food type

2020· article· en· W3083741541 on OpenAlexfundno aff
Olga Panagiotopoulou, José Iriarte-Díaz, Hyab Mehari Abraha, Andrea B. Taylor, Simon Wilshin, Paul C. Dechow, Callum F. Ross

Bibliographic record

VenueJournal of Human Evolution · 2020
Typearticle
Languageen
FieldPsychology
TopicPrimate Behavior and Ecology
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Dental and Craniofacial ResearchCanadian Institutes of Health ResearchMarie CurieNational Institutes of HealthNational Science Foundation
KeywordsSagittal planeTransverse planeAnatomyGeologyMandible (arthropod mouthpart)BiomechanicsMaterials scienceBending momentShear (geology)OrthodonticsStructural engineeringMedicineComposite materialBiologyEngineering

Abstract

fetched live from OpenAlex

Mandible morphology has yet to yield definitive information on primate diet, probably because of poor understanding of mandibular loading and strain regimes, and overreliance on simple beam models of mandibular mechanics. We used a finite element model of a macaque mandible to test hypotheses about mandibular loading and strain regimes and relate variation in muscle activity during chewing on different foods to variation in strain regimes. The balancing-side corpus is loaded primarily by sagittal shear forces and sagittal bending moments. On the working side, sagittal bending moments, anteroposterior twisting moments, and lateral transverse bending moments all reach similar maxima below the bite point; sagittal shear is the dominant loading regime behind the bite point; and the corpus is twisted such that the mandibular base is inverted. In the symphyseal region, the predominant loading regimes are lateral transverse bending and negative twisting about a mediolateral axis. Compared with grape and dried fruit chewing, nut chewing is associated with larger sagittal and transverse bending moments acting on balancing- and working-side mandibles, larger sagittal shear on the working side, and larger twisting moments about vertical and transverse axes in the symphyseal region. Nut chewing is also associated with higher minimum principal strain magnitudes in the balancing-side posterior ramus; higher sagittal shear strain magnitudes in the working-side buccal alveolar process and the balancing-side oblique line, recessus mandibulae, and endocondylar ridge; and higher transverse shear strains in the symphyseal region, the balancing-side medial prominence, and the balancing-side endocondylar ridge. The largest food-related differences in maximum principal and transverse shear strain magnitudes are in the transverse tori and in the balancing-side medial prominence, extramolar sulcus, oblique line, and endocondylar ridge. Food effects on the strain regime are most salient in areas not traditionally investigated, suggesting that studies seeking dietary effects on mandible morphology might be looking in the wrong places.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.834
Threshold uncertainty score0.141

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.024
GPT teacher head0.307
Teacher spread0.282 · 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

Citations30
Published2020
Admission routes1
Has abstractyes

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