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Record W4404717884 · doi:10.1097/won.0000000000001130

Executive Summary: Topical Management of Malignant Cutaneous Wounds

2024· article· en· W4404717884 on OpenAlexaffabout
Valérie Chaplain

Bibliographic record

VenueJournal of Wound Ostomy and Continence Nursing · 2024
Typearticle
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsInternational Game Technology (Canada)Nova Scotia Health AuthorityMontfort HospitalUniversity of LethbridgeToronto Western HospitalCanadian Pacific Railway (Canada)CARE CanadaUniversity Health Network
Fundersnot available
KeywordsMedicineWound careHealth careNursingMEDLINEQuality of life (healthcare)Health professionalsIntensive care medicine

Abstract

fetched live from OpenAlex

Malignant cutaneous wounds pose unique challenges in patient care, requiring specialized attention to alleviate local symptoms and enhance health-related quality of life. As the prevalence of these wounds continues to rise with improving cancer survival rates, it is essential to establish comprehensive best practice recommendations for their topical management. To address this need, a task force was assembled from across Canada, consisting of members from Nurses Specialized in Wound, Ostomy, and Continence Canada and the Canadian Palliative Care Nursing Association. The purpose of these recommendations is to provide a framework for the topical management of malignant cutaneous wounds for health care professionals, emphasizing the substantial role of their support persons. Recognizing the impact of cultural humility and the need to deliver care that respects individual beliefs and practices is crucial in providing effective and equitable care. The 23 presented recommendations aim to guide nurses, the interdisciplinary team, and the health system to enhance the overall quality of malignant cutaneous wound care management.

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)0.008
metaresearch head score (Gemma)0.023
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: Review · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0080.008
Insufficient payload (model declined to judge)0.0350.026

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 head0.015
GPT teacher head0.306
Teacher spread0.292 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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Same venueJournal of Wound Ostomy and Continence NursingSame topicWound Healing and TreatmentsFrench-language works237,207