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Wound bed preparation and oxygen balance – a new component?

2007· article· en· W2119137812 on OpenAlexaff
R. Gary Sibbald, Kevin Woo, Douglas Queen

Bibliographic record

VenueInternational Wound Journal · 2007
Typearticle
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsWomen's College Hospital
Fundersnot available
KeywordsMedicineWound careBalance (ability)SpecialtyIntensive care medicineElement (criminal law)Clinical PracticeBest practiceEngineering ethicsNursingPhysical therapyManagementFamily medicine

Abstract

fetched live from OpenAlex

Chronic wounds have traditionally been treated by conservative means. It was Winter's moist wound healing research, in 1962, that stimulated a proliferation of a moist interactive dressing technologies. Even considering this advancement in thinking, chronic wounds continue to be a problem for many clinicians. An increasing delineation of the science of healing in the past 20 years has redefined the way in which we both evaluate and treat wounds. This scientific understanding has raised wound care from the clinical problem arena to that of clinical specialty, where many now cross refer patients to specialists in this field. Wound bed preparation (WBP) has played a significant role in this change in practice. The concept has changed an 'art' of switching at random from one dressing to another, into a clinical science. WBP has come to the forefront as a major educational aid to help others develop appropriate treatment of the underlying disease causing the wound and patient requirements. The concept of WBP evolved over the recent years, becoming more and more sophisticated with time. Recent adaptations have brought together many of the current components. This article proposes yet another element of WBP, that of 'oxygen balance'.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.147
Threshold uncertainty score0.360

Codex and Gemma teacher scores by category

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

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 head0.024
GPT teacher head0.345
Teacher spread0.321 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations15
Published2007
Admission routes1
Has abstractyes

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