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Record W1894710612

Validation of a finite element code for a continuum model of vocal fold vibration under the influence of a sessile polyp

2015· article· en· W1894710612 on OpenAlexaffvenue
Raymond Greiss, Joana Rocha, Edgar Matida

Bibliographic record

VenueCanadian acoustics · 2015
Typearticle
Languageen
FieldMedicine
TopicVoice and Speech Disorders
Canadian institutionsCarleton University
Fundersnot available
KeywordsFinite element methodVibrationVocal foldsPhonationParameterized complexityAcousticsComputer scienceStructural engineeringPhysicsEngineeringAlgorithmLarynx
DOInot available

Abstract

fetched live from OpenAlex

Vocal fold vibration has been extensively investigated using numerical simulation through the use of lumped element models, and more recently, through the use of finite element continuum models. Finite element models offer the ability to analyze the effects of detailed and complex geometric models, allowing for the study of the influence of pathologies and phonosurgery on the process of phonation. The present study details the development of a finite element code of vocal fold vibration and a continuum model of a vocal fold with a sessile polyp. The capability of the code to capture major structural vibration trends are illustrated through a validation process, wherein previously explored models are replicated, and computed results are sub- sequently compared to gauge the code’s efficacy. An overview of literature pertinent to the modeling of vocal fold polyps is presented, followed by the discussion of the creation of a continuum model of a vocal fold affected by a sessile polyp. This pathological model is parameterized according to the size and position of the polyp, and trends are explored based on varying these parameters. Polyp size is concluded to have a more profound influence on the fundamental frequency of vibration than position. An inversely proportional relationship is found between polyp size and fundamental frequency, as well as proximity to the anterior-posterior surface and fundamental frequency.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.179
Threshold uncertainty score0.786

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 head0.040
GPT teacher head0.283
Teacher spread0.243 · 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

Citations6
Published2015
Admission routes2
Has abstractyes

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