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Record W2806380585 · doi:10.1063/1.5038503

A new finite-element model of the incudostapedial joint

2018· article· en· W2806380585 on OpenAlexaff
Majid Soleimani, W. Robert J. Funnell, Willem F. Decraemer

Bibliographic record

VenueAIP conference proceedings · 2018
Typearticle
Languageen
FieldEngineering
TopicVibration and Dynamic Analysis
Canadian institutionsMcGill University
Fundersnot available
KeywordsJoint (building)Finite element methodCompression (physics)Joint capsuleMaterials scienceSynovial jointStructural engineeringStiffnessTension (geology)Displacement (psychology)MechanicsPhysicsComposite materialAnatomyEngineering

Abstract

fetched live from OpenAlex

Although the joints of the ossicular chain contribute significantly to sound transmission through the middle ear, the mechanical behaviour of these joints is poorly understood. We have previously presented finite-element (FE) models of the incudostapedial joint (ISJ) that were structurally based on histological serial sections and X-ray microCT scans, and that used plausible estimates for material-property parameters. Models with or without the presence of synovial fluid in the joint were made and preliminary simulations were compared with experimental tension and compression measurements. Later we presented an analytical model of the joint with a simplified geometry using the theory of large deformations of elastic membranes to model the joint capsule. Results indicated that the mechanical behaviour of the incudostapedial joint may be influenced by mechanical instabilities of the joint capsule. This was observed for forces near zero in a simulated tension-compression test and could result in a jump in the corresponding force-displacement curve. In this work, we present new finite-element simulations where we model the synovial gap with a liquid-like incompressible material and perform a sensitivity analysis to see the effect of various properties, such as capsule length, synovial-fluid volume, and joint cross-sectional shape on the mechanical behaviour of the joint. The results are compared with experimental results from the literature.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.936
Threshold uncertainty score0.330

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 head0.220
Teacher spread0.196 · 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 designSimulation or modeling
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
Published2018
Admission routes1
Has abstractyes

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