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Record W4402781083 · doi:10.1097/won.0000000000001116

Medical Adhesive-Related Skin Injury at 10 Years

2024· review· en· W4402781083 on OpenAlexaboutno aff
Andrew Barton, Daphne Broadhurst, Jan L. Hitchcock, Carolyn Lund, Laurie McNichol, Catherine R. Ratliff, Juliano Teixeira Moraes, Stephanie Yates, Mikel Gray

Bibliographic record

VenueJournal of Wound Ostomy and Continence Nursing · 2024
Typereview
Languageen
FieldMedicine
TopicSurgical Sutures and Adhesives
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEpidemiologyMEDLINEClinical PracticeFamily medicineMedical educationPolitical sciencePathology

Abstract

fetched live from OpenAlex

Awareness of medical adhesive-related skin injury (MARSI) has increased in the decade since a foundational consensus report was published in 2013. Additional research has provided greater knowledge of the epidemiology of MARSI, along with its assessment, prevention, and management. To summarize knowledge generated in the past decade and review our current understanding of MARSI, a panel of nine clinical experts from four countries (United States of America, United Kingdom, Canada, and Brazil) convened to discuss the literature published since the initial 2013 document and develop updated recommendations for clinical practice. The group formulated 20 updated consensus statements covering the assessment, prevention, and management of skin injuries related to adhesive medical devices and proposed next steps to address remaining gaps in research and knowledge of this complex and clinically relevant condition.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.353
Teacher spread0.334 · 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 teacher head, not a consensus.

Study designOther design
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

Citations23
Published2024
Admission routes1
Has abstractyes

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