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Record W2799357830 · doi:10.12968/pnur.2018.29.5.223

Treating eczema in children in general practice

2018· article· en· W2799357830 on OpenAlexaff
Julie Van Onselen

Bibliographic record

VenuePractice Nursing · 2018
Typearticle
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsLearning Partnership
Fundersnot available
KeywordsMedicinePrimary careAsthmaAsthma managementFamily medicineDisease managementChronic diseasePediatricsDiseaseImmunologyPathology

Abstract

fetched live from OpenAlex

Atopic eczema is very common and the vast majority of children are treated in primary care. Julie Van Onselen highlights the key role practice nurses can play in helping to manage eczema Atopic eczema is very common in children and the vast majority are treated in primary care. Atopic eczema management mirrors management of chronic asthma in primary care. Practice nurses are well placed to be ‘atopic nurses’ and assess, educate and treat children with atopic eczema, in a framework of chronic disease management, as they do in asthma management. This article gives information on assessment, the stepped approach to atopic eczema management, and discusses adherence and education of parents/carers, children and families.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.015
GPT teacher head0.367
Teacher spread0.352 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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