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Record W4412975868 · doi:10.1121/10.0037467

Gender and lesion characteristics modulate the sibilant acoustics in continuous speech after tongue cancer surgery

2025· article· en· W4412975868 on OpenAlexaffabout
Gillian de Boer, Daniel Aalto

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2025
Typearticle
Languageen
FieldMedicine
TopicVoice and Speech Disorders
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCogContext (archaeology)MedicineTongueLesionCancerAudiologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

Oral and oropharyngeal cancer and its treatment can have a devastating impact on speech. The acoustics of 4385 productions of /s/ from 89 patients (66M,23F) mean age 58.67 (range 22–82 years) were analyzed before and after (1, 6, and 12 months) glossectomy surgery. Center of gravity of the fricative power spectrum (COG) was analyzed with a linear mixed effects model with assessment time, age, gender, and amounts of resections (%) within oral and pharyngeal structures as fixed effects and random intercepts for speaker and phonetic context. Before surgery, greater tumor invasion into the floor of the mouth, male sex, and older age lowered the COG. After surgery, COG was reduced (1 month: 1900 Hz; 6 months: 1520 Hz; 1 year: 1080 Hz) and dropped more for women than men. Lesion site impacts COG: the greater the tumour invasion in the tongue, the more the 1-month COG was lowered compared to the rest of the model pointing to a transient aggravating effect. The results suggest partial recovery of speech function at 1 year. The recovery is gendered with women remaining further away from the pre-treatment values after surgery. Future analysis will consider the effects of chemo-therapy and radiation. [Work supported by the Alberta Cancer Foundation, Grant RES0061908.]

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.576
Threshold uncertainty score0.266

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.018
GPT teacher head0.285
Teacher spread0.267 · 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 designObservational
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
Published2025
Admission routes2
Has abstractyes

Explore more

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