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Pressure Ulcer Staging Revisited

2011· review· en· W2335261064 on OpenAlex
R. Gary Sibbald, D Krasner, Kevin Woo

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

VenueAdvances in Skin & Wound Care · 2011
Typereview
Languageen
FieldHealth Professions
TopicPressure Ulcer Prevention and Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineGrading (engineering)Continuing educationCompetence (human resources)Wound careDocumentationSurgeryMedical educationComputer science

Abstract

fetched live from OpenAlex

In Brief PURPOSE: To enhance the learner’s competence with knowledge about superficial skin changes and deep pressure ulcer (PrU) framework concepts as compared with the currently used PrU staging and grading classification system TARGET AUDIENCE: This continuing education activity is intended for physicians and nurses with an interest in skin and wound care. OBJECTIVES: After participating in this educational activity, the participant should be better able to: Examine the physiologic changes and causes of superficial skin changes and deep PrUs. Demonstrate advantages of using the superficial skin changes and deep PrU framework for documentation. Deficiencies in the current pressure ulcer classification system create the impetus for the current discourse on the clinical, legal, and economic implications of staging and considering shifting the paradigm in pressure ulcer description and assessment. This continuing education activity reviews a proposed conceptual framework to describe superficial moisture and friction changes and deep tissue damage (often pressure and shear related).

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)0.001
metaresearch head score (Gemma)0.000
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 score0.961
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.059
GPT teacher head0.464
Teacher spread0.405 · 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