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Record W2139551838

On the influence of the material properties of the external ear on occlusion effect simulations

2012· article· en· W2139551838 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian acoustics · 2012
Typearticle
Languageen
FieldMedicine
TopicReconstructive Facial Surgery Techniques
Canadian institutionsÉcole de Technologie Supérieure
FundersInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail
KeywordsPoisson's ratioCadaverBiomedical engineeringMaterial propertiesModulusMaterials scienceFractional factorial designPoisson distributionSoft tissueAnatomyHead (geology)Factorial experimentMathematicsComposite materialMedicineStatisticsGeologySurgery
DOInot available

Abstract

fetched live from OpenAlex

A two-level fractional factorial design was implemented to examine how the material properties of the external ear tissues influence numerical predictions of the occlusion effect (OE). A simplified 2D model was developed and successfully compared to an equivalent 3D model whose complex external ear geometry was reconstructed using 135 anatomical images of a female cadaver head. Outer circumferential boundaries of the skin and cartilage domains are fixed. Analysis of variance indicates significant single factor effects for skin, soft, and bony tissues. Skin, soft, and bony material properties are found to contribute significantly to simulated OEs. Mostly Poisson's ratio and Young's modulus of the skin tissue tend to exhibit effect estimates which are large enough to cause relevant variations in simulated OE data.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.589
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.012
GPT teacher head0.232
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