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Record W2524088674

Validation of a Finite Element Continuum Model of Vocal Fold Vibration

2014· article· en· W2524088674 on OpenAlexaff
Raymond Greiss, Joana Rocha, Edgar Matida

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicVoice and Speech Disorders
Canadian institutionsCarleton University
Fundersnot available
KeywordsVocal foldsFinite element methodVibrationConvergence (economics)Vocal tractComputer scienceFold (higher-order function)AlgorithmMathematicsAcousticsPhysicsStructural engineeringSpeech recognitionEngineering
DOInot available

Abstract

fetched live from OpenAlex

Vocal fold dynamics have been explored extensively in recent years using both reduced-order coupled mass and continuum models. These models have been used for analysis of phonosurgeries and pathologies, and accordingly, require greater resolution and progressive simulation techniques to capture the defining characteristics of pathological and/or uncommon speech. The following work offers a contribution to the advancement of the aforementioned models through the development and validation of an in-house finite element model which captures the influence of a sessile vocal fold polyp. A validation of the adopted finite element formulation is presented through replication of previous computational studies on vocal folds under free vibration conditions. Natural frequencies and mode shapes are extracted from the computed eigensystems and subsequently compared with these studies to legitimize the formulation of the system’s equation of motion and the corresponding numerical solution. Convergence behaviour and accuracy of these analyses are used to justify the choice of formulation in the development of the code. The development of a model of a sessile polyp is documented, and a brief analysis of this system is presented. Fundamental frequency magnitude is found to be inversely proportional to polyp size, and at a minimum for the case of a polyp centered along the length of the vocal fold.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.367
Threshold uncertainty score0.143

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 head0.021
GPT teacher head0.265
Teacher spread0.244 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

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