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Record W2313029145 · doi:10.1177/000348940411301001

Functional Outcomes of Reduced Hyaluronan in Acute Vocal Fold Scar

2004· article· en· W2313029145 on OpenAlexfundno aff
Bernard Rousseau, Jin-Ho Sohn, Ichiro Tateya, Douglas W. Montequin, Diane M. Bless

Bibliographic record

VenueAnnals of Otology Rhinology & Laryngology · 2004
Typearticle
Languageen
FieldMedicine
TopicVoice and Speech Disorders
Canadian institutionsnot available
FundersNational Institute on Deafness and Other Communication DisordersRyerson University
KeywordsPhonationVocal foldsLarynxHyaluronic acidMedicineWound healingScar tissuePathologyAnatomySurgeryAudiology

Abstract

fetched live from OpenAlex

To examine the functional effects of hyaluronan and collagen alterations in acute vocal fold scar, we injured 15 pig larynges by vocal fold mucosa stripping. At 3, 10, and 15 days after operation, we performed excised larynx experiments to measure phonation threshold pressure (PTP) and vocal economy (an acoustic output-cost ratio; OCR), and then performed hyaluronan and collagen assays. Five uninjured larynges were used as excised controls. Hyaluronan was reduced in the scarred vocal folds through 15 days of wound healing. Collagen was increased at day 15. The PTP was increased and OCR was decreased in scarred larynges, indicating decreased vocal efficiency and ease of phonation. Thus, PTP and OCR were sensitive to the biomolecular changes in acute vocal fold scar. Hyaluronan was more susceptible than collagen to acute tissue ultrastructural alterations. These findings may provide a rationale for increasing hyaluronan in acute vocal fold scar to improve postoperative vocal outcomes.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.048
GPT teacher head0.331
Teacher spread0.283 · 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 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

Citations55
Published2004
Admission routes1
Has abstractyes

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