MétaCan
Menu
Back to cohort
Record W2035048077 · doi:10.1115/biomed2007-38077

Intra-Operative Laryngoscopic Instrument for Characterizing Vocal Fold Viscoelasticity

2007· article· en· W2035048077 on OpenAlexaff
Mark P. Ottensmeyer, Michael C. Yip, Conor J. Walsh, James B. Kobler, James T. Heaton, Steven M. Zeitels

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicVoice and Speech Disorders
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsVocal foldsLarynxPhonationLamina propriaFold (higher-order function)Human voiceViscoelasticitySpeech recognitionVocal tractAcousticsComputer scienceMaterials scienceBiomedical engineeringAnatomyPhysicsBiologyAudiologyMedicineEpitheliumPathologyComposite material

Abstract

fetched live from OpenAlex

Our society depends on communication, the most natural form of which is speech. Trauma, disease and the normal aging process will cause many to suffer degraded or lost vocal fold function, and it has been observed that this number is growing [1]. The vocal folds are the vibrating structures in the larynx that enable us to generate voice, from speech to opera singing. The vibrating portions of the folds consist of an external 0.1mm thick layer of epithelial cells, a soft, gel-like 0.5mm thick layer called the lamina propria (LP), a 0.3mm thick vocal ligament and an underlying thyroarytenoid muscle [2]. The fundamental frequency of speech in men is in the 100–150Hz range, and between 200 and 300Hz in women [3].

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)0.001
metaresearch head score (Gemma)0.002
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 score0.009
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.023
GPT teacher head0.316
Teacher spread0.293 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

Explore more

Same topicVoice and Speech DisordersFrench-language works237,207