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Record W2464897739 · doi:10.1097/der.0000000000000192

Current Quality-of-Life Tools Available for Use in Contact Dermatitis

2016· review· en· W2464897739 on OpenAlexvenueno aff
Jacquelyn M. Swietlik, Margo J. Reeder

Bibliographic record

VenueDermatitis · 2016
Typereview
Languageen
FieldMedicine
TopicContact Dermatitis and Allergies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineQuality of life (healthcare)DermatologyContact dermatitisDiseaseIrritant contact dermatitisConsistency (knowledge bases)PathologyImmunologyAllergy

Abstract

fetched live from OpenAlex

Contact dermatitis is a common dermatologic condition that can cause significant impairment in patients' overall quality of life (QoL). This impact is separate and potentially more clinically relevant than one's disease "severity" in contact dermatitis and should be consistently addressed by dermatologists. Despite this, QoL tools specific to contact dermatitis are lacking, and there is little consistency in the literature regarding the tool used to evaluate clinical response to therapies. Measurements currently available to evaluate disease-related QoL in contact dermatitis fit into 1 of the following 3 general types: generic health-related QoL measures, dermatology-related QoL measures, or specific dermatologic disease-related QoL measures. This article reviews the strengths and weaknesses of existing QoL tools used in contact dermatitis including: Short Form Survey 36, Dermatology Life Quality Index, Skindex-29, Skindex-16, Dermatology-Specific Quality of Life, and Fragrance Quality of Life Index.

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.008
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.163
GPT teacher head0.383
Teacher spread0.220 · 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 designSystematic review
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

Citations23
Published2016
Admission routes1
Has abstractyes

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