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Record W2005369678 · doi:10.1002/cnm.1423

Coupled hard–soft tissue simulation with contact and constraints applied to jaw–tongue–hyoid dynamics

2010· article· en· W2005369678 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternational Journal for Numerical Methods in Biomedical Engineering · 2010
Typearticle
Languageen
FieldHealth Professions
TopicTemporomandibular Joint Disorders
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTonguePoint (geometry)Constraint (computer-aided design)Finite element methodHyoid boneComputer scienceStructural engineeringEngineeringMechanical engineeringAnatomyGeometryMathematicsMedicine

Abstract

fetched live from OpenAlex

Abstract We present an open‐source physical simulation system suitable for efficient modeling of anatomical structures composed of both hard and soft tissue components, interconnected by point‐wise attachments, contact, and other constraints. Specific attention is paid to the computational formulation needed for the coupled simulation of rigid and deformable structures, and a constraint‐based mechanism is described for attaching these together. As an application of this system, we then present a novel 3D dynamic model of the jaw–tongue–hyoid complex, consisting of an FEM model of the tongue, rigid jaw, and hyoid structures, point‐to‐point muscle actuators, and constraints for bite contact and the temporomandibular joints. Several simulations are presented showing combined jaw–tongue actions and demonstrating the effects of coupled jaw–tongue–hyoid dynamics. Copyright © 2010 John Wiley & Sons, Ltd.

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.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.854
Threshold uncertainty score0.737

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
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 integrity0.0000.001
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 head0.026
GPT teacher head0.456
Teacher spread0.430 · 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