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Record W3200557775 · doi:10.1055/s-0041-1731463

Comparison of Skin Substitutes for Acute and Chronic Wound Management

2021· review· en· W3200557775 on OpenAlexaff
Caroline C. Bay, Zachary Chizmar, Edward M. Reece, Jessie Z. Yu, Julian Winocour, Joshua Vorstenbosch, Sebastian Winocour

Bibliographic record

VenueSeminars in Plastic Surgery · 2021
Typereview
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineChronic woundDermatologyIntensive care medicineWound healingSurgery

Abstract

fetched live from OpenAlex

Chronic and acute wounds, such as diabetic foot ulcers and burns, respectively, can be difficult to treat, especially when autologous skin transplantations are unavailable. Skin substitutes can be used as a treatment alternative by providing the structural elements and growth factors necessary for reepithelialization and revascularization from a nonautologous source. As of 2020, there are 76 commercially available skin substitute products; this article provides a review of the relevant literature related to the major categories of skin substitutes available.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.072
GPT teacher head0.410
Teacher spread0.338 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations49
Published2021
Admission routes1
Has abstractyes

Explore more

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