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Record W2032823608 · doi:10.1016/j.otohns.2006.11.022

Quantitative Three‐Dimensional Ultrasound Imaging of Partially Resected Tongues

2007· article· en· W2032823608 on OpenAlexaff
Tim Bressmann, Elizabeth Ackloo, Chiang‐Le Heng, Jonathan C. Irish

Bibliographic record

VenueOtolaryngology · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCleft Lip and Palate Research
Canadian institutionsPrincess Margaret Cancer CentreToronto General HospitalUniversity Health NetworkUniversity of Toronto
FundersNational Institutes of Health
KeywordsTongueMedicineGlossectomyAnatomyUltrasoundRadiologyPathology

Abstract

fetched live from OpenAlex

OBJECTIVE: We sought to assess the impact of partial lateral glossectomies on tongue function and speech. STUDY DESIGN AND SETTING: Tongue shapes of 12 patients with lateral tumors of the tongue were recorded with three-dimensional ultrasound before their surgery and two months after. Twelve normal participants served as controls. Speech acceptability was also assessed. RESULTS: Principal component analyses demonstrated that the flap reconstructions led to a stiffening of the operated side of the tongue. A concavity index and an asymmetry index demonstrated that the glossectomy patients exhibited decreased midsagittal grooving and increased lingual asymmetry. The change in midsagittal grooving correlated moderately with the decrease in speech acceptability. CONCLUSION: A lateral partial glossectomy affects the tongue's intrinsic deformation, in particular midsagittal grooving and symmetry. This can have a detrimental effect for speech. SIGNIFICANCE: A lateral resection affects the tongue's symmetry and midsagittal groove. The change in midsagittal grooving correlates with a decrease in speech acceptability.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.020
GPT teacher head0.314
Teacher spread0.294 · 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 source (direct Gemma or distilled Codex), 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

Citations52
Published2007
Admission routes1
Has abstractyes

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