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Record W2128710325 · doi:10.1002/polb.22396

Fabrication of 3D electrospun structures from poly(lactide‐<i>co</i>‐glycolide acid)–nano‐hydroxyapatite composites

2011· article· en· W2128710325 on OpenAlex
Linus H. Leung, Stephanie Fan, Hani E. Naguib

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Polymer Science Part B Polymer Physics · 2011
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsUniversity of TorontoUniversity of New Brunswick
FundersCanada Foundation for Innovation
KeywordsFabricationMaterials scienceElectrospinningComposite materialPorosityComposite numberPLGAUltimate tensile strengthNanoparticlePolymerNanotechnology

Abstract

fetched live from OpenAlex

Abstract The fabrication of three‐dimensional (3D) electrospun composite scaffolds was presented in this study. Layers of electrospun meshes made from composites of poly(lactide‐ co ‐glycolide acid) (PLGA) and hydroxyapatite (HA) were stacked and sintered using pressurized gas. Three HA concentrations of 5, 10, and 20 wt % were tested, and the addition of the HA nanoparticles decreased the tensile mechanical properties of the meshes with 20 wt % HA. However, after the gas absorption process, the fibers within the mesh sintered, which improved the mechanical properties more than twofold. The fabrication of 3D, porous, electrospun scaffolds was also demonstrated. The resulting 3D scaffolds had open porosity of up to 70% and modulus of ∼20 MPa. This technique improves on the current electrospinning technology by overcoming the challenges of depositing a thick, 3D structure. © 2011 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys, 2011

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)0.001
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 score0.060
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.015
GPT teacher head0.260
Teacher spread0.245 · 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