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Record W2155243994 · doi:10.1002/mabi.200700002

Macromolecular Biomaterials for Scaffold‐Based Vascular Tissue Engineering

2007· review· en· W2155243994 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

VenueMacromolecular Bioscience · 2007
Typereview
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsScaffoldRegeneration (biology)Tissue engineeringIn vivoBiomedical engineeringNanotechnologyChemistryMedicineMaterials scienceCell biologyBiologyBiotechnology

Abstract

fetched live from OpenAlex

Cardiovascular diseases are increasingly becoming the main cause of death all over the world, which has led to an increase in the economic and social burden of such diseases. Vascular tissue engineering (VTE) is providing a route towards interesting applications, mainly focussing on the in vitro, in vivo, or combined in vitro/in vivo regeneration of small-diameter blood vessels (<6 mm) for coronary or peripheral vascular substitutions. Although different approaches have been investigated in the past two decades to achieve this aim, the most common method uses a macromolecular-based structure to scaffold cells during the regeneration process. Therefore, the aim of this work is to comprehensively review macromolecular biomaterials that were designed, developed, fabricated, and tested for scaffolding VTE. In an effort to provide a comprehensive overview, this review will mainly focus on the mechanical properties of the construct and its biological performance that results from the scaffold colonization during cell growth.

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)0.000
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.659
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0030.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.030
GPT teacher head0.342
Teacher spread0.312 · 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