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Record W3200649072 · doi:10.32393/csme.2021.78

Characterization Of A Tissue-Like Hyperelastic Polymer

2021· article· en· W3200649072 on OpenAlexaff
Stephanie Gibbons, Sam Nakhla, Ahmed Elruby, Adam Dubrowski

Bibliographic record

VenueProgress in Canadian Mechanical Engineering. Volume 4 · 2021
Typearticle
Languageen
FieldEngineering
TopicElasticity and Material Modeling
Canadian institutionsOntario Tech UniversityMemorial University of Newfoundland
Fundersnot available
KeywordsHyperelastic materialCharacterization (materials science)PolymerMaterials scienceComputer scienceComposite materialPolymer scienceEngineeringNanotechnologyFinite element methodStructural engineering

Abstract

fetched live from OpenAlex

Abdominal Aortic Aneurysms (AAAs) are an often fatal medical condition that frequently remains asymptomatic.There is considerable interest in research associated with AAAs as they have a reported mortality rate of up to 90% in the event of rupture.Most present studies completed on AAAs are in silico due to the challenges associated with using human tissue, or human participants.These studies mainly consist of computer simulations, modelling the AAA as a hyperelastic material, many of which rely on the same material strain energy function (SEF) that was introduced in literature.However, to date no in vitro studies have been completed to validate these computational models.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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

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 head0.006
GPT teacher head0.191
Teacher spread0.185 · 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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueProgress in Canadian Mechanical Engineering. Volume 4Same topicElasticity and Material ModelingFrench-language works237,207