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Record W2318615640 · doi:10.1515/epoly-2014-0137

Characterization of auxetic polyurethanes foam for biomedical implants

2014· article· en· W2318615640 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.

Bibliographic record

Venuee-Polymers · 2014
Typearticle
Languageen
FieldEngineering
TopicCellular and Composite Structures
Canadian institutionsUniversity of Victoria
FundersUniversity of Bolton
KeywordsAuxeticsMaterials scienceSoft tissuePolyurethaneCompressibilityComposite materialElasticity (physics)Deformation (meteorology)Characterization (materials science)Biomedical engineeringNanotechnologyMedicineSurgeryMechanics

Abstract

fetched live from OpenAlex

Abstract Aging, accidents and diseases are the leading causes of disability in today’s world. Therefore, implants and prostheses for hard and soft tissues are becoming increasingly common to restore daily activity and improve the quality of life of patients. Although implants have been extensively developed and are in the clinical use, deformation mechanism, inflexibility and mismatch of the elastic and mechanical behavior of the implants with native tissues are challenges for tissue engineering. The objective of this study was to characterize auxetic polyurethane foam as an auxetic soft tissue implant based on mathematical modeling using a nonlinear elasticity theory. The compressibility effects on auxetic soft tissue implants due to equibiaxial loading were studied. Numerical results were computed using experimentally obtained data and compared with the non-auxetic behavior of a soft tissue.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.032
Threshold uncertainty score0.329

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 science0.0000.000
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 head0.004
GPT teacher head0.196
Teacher spread0.191 · 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