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Record W2953620536 · doi:10.3390/bioengineering6030056

Sources of Collagen for Biomaterials in Skin Wound Healing

2019· review· en· W2953620536 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

VenueBioengineering · 2019
Typereview
Languageen
FieldMaterials Science
TopicCollagen: Extraction and Characterization
Canadian institutionsSt. Francis Xavier University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWound healingBiomedical engineeringMedicineSurgery

Abstract

fetched live from OpenAlex

Collagen is the most frequently used protein in the fields of biomaterials and regenerative medicine. Within the skin, collagen type I and III are the most abundant, while collagen type VII is associated with pathologies of the dermal-epidermal junction. The focus of this review is mainly collagens I and III, with a brief overview of collagen VII. Currently, the majority of collagen is extracted from animal sources; however, animal-derived collagen has a number of shortcomings, including immunogenicity, batch-to-batch variation, and pathogenic contamination. Recombinant collagen is a potential solution to the aforementioned issues, although production of correctly post-translationally modified recombinant human collagen has not yet been performed at industrial scale. This review provides an overview of current collagen sources, associated shortcomings, and potential resolutions. Recombinant expression systems are discussed, as well as the issues associated with each method of expression.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.973
Threshold uncertainty score0.986

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.059
GPT teacher head0.322
Teacher spread0.262 · 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