MétaCan
Menu
Back to cohort
Record W4401480258 · doi:10.1016/j.jmbbm.2024.106685

Alveolar wall hyperelastic material properties determined using alveolar cluster model with experimental stress-stretch and pressure-volume data

2024· article· en· W4401480258 on OpenAlexafffund
Dilaver Singh, Arthur S. Slutsky, Duane S. Cronin

Bibliographic record

VenueJournal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials · 2024
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHyperelastic materialAlveolar WallMaterials scienceTension (geology)Finite element methodSurface tensionStructural engineeringStress (linguistics)Pulmonary alveolusMechanicsBiomedical engineeringLungComposite materialEngineeringMedicineUltimate tensile strengthThermodynamicsRespiratory disease

Abstract

fetched live from OpenAlex

Micro-scale models of lung tissue have been employed by researchers to investigate alveolar mechanics; however, they have been limited by the lack of biofidelic material properties for the alveolar wall. To address this challenge, a finite element model of an alveolar cluster was developed comprising a tetrakaidecahedron array with the nominal characteristics of human alveolar structure. Lung expansion was simulated in the model by prescribing a pressure and monitoring the volume, to produce a pressure-volume (PV) response that could be compared to experimental PV data. The alveolar wall properties in the model were optimized to match experimental PV response of lungs filled with saline, to eliminate surface tension effects and isolate the alveolar wall tissue response. When simulated in uniaxial tension, the model was in agreement with reported experimental properties of uniaxial tension on excised lung tissue. The work presented herein was able to link micro-scale alveolar response to two disparate macroscopic experimental datasets (stress-stretch and PV response of lung) and presents hyperelastic properties of the alveolar wall for use in alveolar scale finite element models and multi-scale models. Future research will incorporate surface tension effects, and investigate alveolar injury mechanisms.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.029
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.263
Teacher spread0.230 · 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.

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

Citations6
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materialsSame topicHydraulic and Pneumatic SystemsFrench-language works237,207