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Record W2041644614 · doi:10.1121/1.4783150

Experimental and numerical determination of the surface deformation of a synthetic model of the human vocal folds.

2008· article· en· W2041644614 on OpenAlexaff
Li‐Jen Chen, Luc Mongeau

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2008
Typearticle
Languageen
FieldComputer Science
TopicSpeech Recognition and Synthesis
Canadian institutionsMcGill University
Fundersnot available
Keywordsvon Mises yield criterionMaterials scienceSynthetic dataMechanicsDeformation (meteorology)Vocal foldsStress (linguistics)Displacement (psychology)AcousticsOscillation (cell signaling)Experimental dataAmplitudeSurface (topology)Finite element methodComputer scienceOpticsMathematicsGeometryPhysicsAlgorithmComposite materialThermodynamics

Abstract

fetched live from OpenAlex

A model of human vocal folds was fabricated using a three-component liquid platinum-catalyzed silicone solution. The size, idealized shape, and mechanical properties of the homogeneous synthetic model were selected based on the available data. The superior surface displacement of the synthetic model during self-oscillations was measured using the digital image correlation technique. A finite element model of the synthetic model was created to calculate the state of the deformable solid. Modal testing of the synthetic model was performed to establish the material properties and to verify boundary conditions in the simulation. The self-oscillation of the synthetic model was simulated by imposing a sinusoidal pressure loading over model surfaces, with frequency and amplitude determined from the direct measurement. From the simulation, the von Mises stress over the inferior surface was found to be around 2.2 kPa during the maximum orifice opening, which is around twice of that over the superior surface. So far, only the superior surface deformation data have been available because of technical limitations in clinical studies. The current study may provide additional information, such as the maximum amplitude and location of the peak stress, which is useful for diagnostic and treatment purposes. [Work supported by NIH.]

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.752
Threshold uncertainty score0.369

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.254
Teacher spread0.230 · 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 designBench or experimental
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

Citations0
Published2008
Admission routes1
Has abstractyes

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