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Record W2530432288 · doi:10.1080/21592535.2016.1231276

Fabrication and surface modification of poly lactic acid (PLA) scaffolds with epidermal growth factor for neural tissue engineering

2016· article· en· W2530432288 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBiomatter · 2016
Typearticle
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsNew World LaboratoriesPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsZoomJavaScriptClick chemistryComputer scienceFabricationFeature (linguistics)ChemistryProgramming languageBiologyPolymer chemistry

Abstract

fetched live from OpenAlex

In an effort to design biomaterials that may promote repair of the central nervous system, 3-dimensional scaffolds made of electrospun poly lactic acid nanofibers with interconnected pores were fabricated. These scaffolds were functionalized with polyallylamine to introduce amine groups by wet chemistry. Experimental conditions of the amination protocol were thoroughly studied and selected to introduce a high amount of amine group while preserving the mechanical and structural properties of the scaffold. Subsequent covalent grafting of epidermal growth factor was then performed to further tailor these aminated structures. The scaffolds were then tested for their ability to support Neural Stem-Like Cells (NSLCs) culture. Of interest, NSLCs were able to proliferate on these EGF-grafted substrates and remained viable up to 14 d even in the absence of soluble growth factors in the medium.

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 score0.137
Threshold uncertainty score0.302

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 head0.014
GPT teacher head0.247
Teacher spread0.233 · 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