MétaCan
Menu
Back to cohort
Record W4401027610 · doi:10.1016/j.heares.2024.109092

Finite-element modelling of interactions of needle with tympanic membrane and middle ear

2024· article· en· W4401027610 on OpenAlexaff
Hossein Mohammadi, Arash Ebrahimian, Nima Maftoon

Bibliographic record

VenueHearing Research · 2024
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Resonator Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMiddle earInner earGerbilFinite element methodMembraneAnatomy3d printedBiomedical engineeringMaterials scienceMedicineBiologyEngineeringStructural engineering

Abstract

fetched live from OpenAlex

-order Ogden hyperelastic material and its properties were obtained by fitting to the experimental force-displacement plots of large deformation in the TM under needle indentation. The cohesive parameters were also acquired by calibrating the puncture force against the experimental data of needle insertion into the TM. These FE models were then used to obtain the deformation behaviour of the TM and other middle-ear structures due to the insertion force applied at different locations on the TM. Moreover, we investigated the effect of the TM thickness, the geometry of the needle (i.e., diameter and tip angle), and needle material on the insertion of needles into the TM. We also studied the penetration success of deformable needles.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.000
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 head0.148
GPT teacher head0.325
Teacher spread0.177 · 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 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

Citations4
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueHearing ResearchSame topicAcoustic Wave Resonator TechnologiesFrench-language works237,207