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Record W4408019201 · doi:10.70472/msvt5658

New best practice recommendations For the prevention and management of wounds related to lower limb lymphedema

2025· article· en· W4408019201 on OpenAlexaboutno aff
David Keast, Janet L. Kuhnke

Bibliographic record

VenuePathways. · 2025
Typearticle
Languageen
FieldMedicine
TopicLymphatic System and Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsLymphedemaMedicineLower limbPhysical medicine and rehabilitationPhysical therapyIntensive care medicineSurgeryInternal medicineCancer

Abstract

fetched live from OpenAlex

Wounds Canada is pleased to present new Best Practice Recommendations for the Prevention and Management of Wounds Related to Lower Limb Lymphedema. The Best Practice Recommendations For Skin Health And Wound Management 2025 is the latest version of Wounds Canada’s most popular resource, used by frontline clinicians, students and policy makers to inform their practice.1 These best practice recommendations are focused on the care of adults and the related wounds of the lower limb.

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)0.015
metaresearch head score (Gemma)0.087
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.288
Threshold uncertainty score0.572

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.087
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0060.006
Science and technology studies0.0030.002
Scholarly communication0.0050.004
Open science0.0060.003
Research integrity0.0110.015
Insufficient payload (model declined to judge)0.0470.022

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 head0.033
GPT teacher head0.343
Teacher spread0.311 · 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
GenreOther

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

Citations0
Published2025
Admission routes1
Has abstractyes

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