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Record W48639200 · doi:10.1089/ten.teb.2013.0452

Control of Scaffold Degradation in Tissue Engineering: A Review

2014· review· en· W48639200 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

VenueTissue Engineering Part B Reviews · 2014
Typereview
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsUniversity of Saskatchewan
FundersSaskatchewan Health Research Foundation
KeywordsScaffoldTissue engineeringBiomaterialContext (archaeology)Regeneration (biology)Biomedical engineeringBiochemical engineeringFunction (biology)EngineeringComputer scienceCell biologyBiology

Abstract

fetched live from OpenAlex

Tissue engineering has shown a great promise as a solution to the high demand for tissue and organ transplantations. Biomaterial scaffolds serve to house and direct cells to grow, exposing them to an adequate perfusion of nutrients, oxygen, metabolic products, and appropriate growth factors to enhance their differentiation and function. The degradation of biomaterial scaffolds is a key factor to successful tissue regeneration. In this article, the existing degradation control approaches in the context of scaffold tissue engineering were reviewed and a new paradigm of thinking called active control of scaffold degradation, proposed elsewhere by us, was also revisited and discussed in light of its benefit and requirement of this new technology.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.877
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.026
GPT teacher head0.316
Teacher spread0.290 · 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