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Record W2090921706 · doi:10.1121/1.2920956

A nonlinear finite-element model of the newborn middle ear

2008· article· en· W2090921706 on OpenAlexaff
Qi Li, W. Robert J. Funnell, Sam J. Daniel

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2008
Typearticle
Languageen
FieldMedicine
TopicEar Surgery and Otitis Media
Canadian institutionsMcGill University
Fundersnot available
KeywordsMiddle earMalleusVolume (thermodynamics)Finite element methodDisplacement (psychology)Materials scienceOssiclesEar canalAnatomyIncusStapesNonlinear systemHyperelastic materialAcousticsMedicinePhysics

Abstract

fetched live from OpenAlex

A three-dimensional static nonlinear finite-element model of a 22-day-old newborn middle ear is presented. The model includes the tympanic membrane (TM), malleus, incus, and two ligaments. The effects of the middle-ear cavity are taken into account indirectly. The geometry is based on a computed-tomography scan and on the published literature, supplemented by histology. A nonlinear hyperelastic constitutive law is applied to model large deformations. The middle-ear cavity and the Young's modulus of the TM have significant effects on TM volume displacements. The TM volume displacement and its nonlinearity and asymmetry increase as the middle-ear cavity volume increases. The effects of the Young's moduli of the ligaments and ossicles are found to be small. The simulated TM volume changes do not reach a plateau when the pressure is varied to either -3 kPa or +3 kPa, which is consistent with the nonflat tails often found in tympanograms in newborns. The simulated TM volume displacements, by themselves and also together with previous ear-canal model results, are compared with equivalent-volume differences derived from tympanometric measurements in newborns. The results suggest that the canal-wall volume displacement makes a major contribution to the total canal volume change, and may be larger than the TM volume displacement.

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)0.001
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: Empirical
Teacher disagreement score0.633
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.035
GPT teacher head0.254
Teacher spread0.219 · 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

Citations30
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicEar Surgery and Otitis MediaFrench-language works237,207