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Record W2023024786 · doi:10.1121/1.3249520

Estimation of the contact pressure on the medial surface of the vocal folds during phonation.

2009· article· en· W2023024786 on OpenAlexaff
Li‐Jen Chen, Luc Mongeau

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2009
Typearticle
Languageen
FieldMedicine
TopicVoice and Speech Disorders
Canadian institutionsMcGill University
Fundersnot available
KeywordsPhonationVocal foldsAcousticsCollisionComputer scienceWork (physics)PhysicsLarynxAudiologyMedicine

Abstract

fetched live from OpenAlex

Voice production involves flow-induced self-oscillations of the vocal folds. Collision between the vocal folds is commonly observed during normal phonation. The contact pressure experienced by human vocal folds during collision is usually considered as the most likely source of phonotrauma. The goal of the present study was to quantify contact pressures in human subjects during phonation. A pressure sensor was developed for direct measurements. Verification data and preliminary data on human subjects were obtained. Subject response and other clinical challenges lead to the development of a less intrusive approach for the contact pressure estimation from high speed images based on a Hertzian impact model. A verification of the accuracy of this approach was made. Results from the nonintrusive approach were compared with results from direct measurements using a hemilaryngeal physical model of the human vocal folds. The experimental setup was designed to reduce sensor’s interference with the vocal fold oscillations. The accuracy of the estimated contact pressure from the nonintrusive method was found to be within around 10%. Advantages and possible sources of error are discussed. [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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.501
Threshold uncertainty score0.269

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 science0.0010.000
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 head0.009
GPT teacher head0.255
Teacher spread0.246 · 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
Published2009
Admission routes1
Has abstractyes

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