MétaCan
Menu
Back to cohort
Record W2013030416 · doi:10.1121/1.4806409

Sound transmission in a simple model of the ear canal and tympanic membrane

2013· article· en· W2013030416 on OpenAlexaff
Antonio González-Herrera, Kapil Wattamwar, Christopher Bergevin, Elizabeth S. Olson

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2013
Typearticle
Languageen
FieldComputer Science
TopicSpeech and Audio Processing
Canadian institutionsYork University
Fundersnot available
KeywordsEardrumAcousticsSound transmission classSound pressurePhysicsPiston (optics)Sound (geography)Transmission (telecommunications)Space (punctuation)Middle earBroadbandOpticsMaterials scienceComputer scienceTelecommunicationsAnatomy

Abstract

fetched live from OpenAlex

The classic picture of middle ear (ME) transmission has the tympanic membrane (TM) as a piston and the ME space as a vacuum. However, the TM moves in a complex wavy pattern and modern theories link this behavior to the ME’s broadband transmission [e.g., Fay et al, Proc. Natl. Acad. Sci. U.S.A. (2006), Parent and Allen, J. Acoust. Soc. Am. (2007)]. Furthermore, Rabbitt [J. Acoust. Soc. Am. (1990)] predicted that the TM radiated considerable sound pressure into the ME space that could in return affect TM motion. This study explores these ideas with a simple model, using a tube terminated with a plastic membrane to model the EC and TM. We measured membrane motion via laser interferometry, and pressure (on both sides) via micro-sensors that allowed positioning very close to the membrane (10 micrometers) without disturbance. We made a finite element model of the system to complement the experimental results. The theoretical results show the interaction of acoustic and mechanical resonances, and both theoretical and experimental results show strong transmission of sound through the membrane at some of its resonant frequencies.

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)0.000
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: Empirical · Consensus signal: none
Teacher disagreement score0.830
Threshold uncertainty score0.184

Codex and Gemma teacher scores by category

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 science0.0010.000
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 head0.013
GPT teacher head0.233
Teacher spread0.220 · 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 designSimulation or modeling
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

Citations1
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicSpeech and Audio ProcessingFrench-language works237,207