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Record W2044997519 · doi:10.1002/jbm.b.30543

Anisotropic polyvinyl alcohol hydrogel for cardiovascular applications

2006· article· en· W2044997519 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

VenueJournal of Biomedical Materials Research Part B Applied Biomaterials · 2006
Typearticle
Languageen
FieldEngineering
TopicElasticity and Material Modeling
Canadian institutionsWestern University
Fundersnot available
KeywordsPolyvinyl alcoholMaterials scienceSelf-healing hydrogelsIsotropyAnisotropyComposite materialPolymerTemperature cyclingThermalPolymer chemistry

Abstract

fetched live from OpenAlex

Polyvinyl alcohol (PVA) is a hydrophilic polymer with various characteristics desired for biomedical applications and can be transformed into a solid hydrogel by physical crosslinking, using a low-temperature thermal cycling process. As with most polymeric materials, the mechanical properties of the resultant PVA are isotropic, as oppose to most soft tissues, which are anisotropic. The objective of this research is to develop a PVA-based hydrogel that not only mimics the nonlinear mechanical properties displayed by cardiovascular tissues, but also their anisotropic behavior. By applying a controlled strain to the PVA samples, while undergoing low-temperature thermal cycling, we were able to create oriented mechanical properties in PVA hydrogels. The oriented stress-strain properties of porcine aorta were matched simultaneously by a PVA hydrogel prepared (10% PVA, cycle 3, 75% initial strain). This novel technique allows the controlled introduction of anisotropy to PVA hydrogel, and gives a broad range of control of its mechanical properties, for specific medical device applications.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.134
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.042
GPT teacher head0.301
Teacher spread0.259 · 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