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Record W2077019628 · doi:10.1080/21681163.2013.851627

Speech function of the oropharyngeal isthmus: a modelling study

2014· article· en· W2077019628 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueComputer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization · 2014
Typearticle
Languageen
FieldMedicine
TopicVoice and Speech Disorders
Canadian institutionsUniversity of SaskatchewanUniversity of British Columbia
FundersNational Institute on Deafness and Other Communication Disorders
KeywordsTongueSoft palateFinite element methodVocal tractFlexibility (engineering)Speech productionComputer scienceNoise (video)AnatomyMaxillaSpeech recognitionMedicineMathematicsEngineeringStructural engineeringArtificial intelligencePathologySurgery

Abstract

fetched live from OpenAlex

A finite element method (FEM) based numerical model of upper airway structures (jaw, tongue, maxilla, soft palate) was implemented to observe interactions between the soft palate and tongue, and in particular to distinguish the contributions of individual muscles in producing speech-relevant constrictions of the oropharyngeal isthmus (OPI), or "uvular" region of the oral tract. Simulations revealed a sphincter-like general operation for the OPI, particularly with regard to the function of the palatoglossus muscle. Further, as has been observed with the lips, the OPI can be controlled by multiple distinct muscular mechanisms, each reliably producing a different sized opening and robust to activation noise, suggestive of a modular view of speech motor control. As off-midline structures of the OPI are difficult to observe during speech production, biomechanical simulation offers a promising approach to studying these structures.

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.

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)0.000
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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.990
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.016
GPT teacher head0.322
Teacher spread0.305 · 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