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Record W2413283423 · doi:10.2310/6620.2009.08084

Patch-Testing with the Standard Series at the Massachusetts General Hospital, 1998 to 2006

2009· article· en· W2413283423 on OpenAlexvenueno aff
Lilla Landeck, Peter C. Schalock, Lynn A. Baden, Konrad Neumann, Ernesto González

Bibliographic record

VenueDermatitis · 2009
Typearticle
Languageen
FieldMedicine
TopicContact Dermatitis and Allergies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePatch testingContact dermatitisPatch testAllergic contact dermatitisPopulationRetrospective cohort studyGeneral hospitalEuropean standardDemographyDermatologyPediatricsAllergySurgeryEnvironmental healthImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: The diagnostic tool to detect allergic contact sensitization is patch testing. OBJECTIVE: Results of patch testing performed from January 1998 to December 2006 at the Massachusetts General Hospital (MGH) are analyzed and compared to our 1990-1997 data as well as to data from North American and European contact dermatitis societies. METHODS: Data were collected from retrospective chart reviews and analyzed, focusing on the Hermal standard tray. RESULTS: The most common sensitizers were fragrance mix (18.3%) and nickel (16.7%). Significant increases over time were seen for balsam of Peru (p < .0005; CI, 1.34-2.76) and wool alcohols (p = .002; CI, 1.38-4.38) while gender-related statistical predominance was seen for nickel in females (p < .0005; CI, 2.92-8.20) and for epoxy resin in males (p < .0005; CI, 0.14-0.58). Our findings are similar to those of the North American and European contact dermatitis societies. The retrospective study sample was drawn from a selected group of referred patients that may not be representative of the general population. Analysis of data focused on the Hermal standard tray and might not reflect trends resulting from additional allergens in supplemental trays. CONCLUSION: Sensitization rates and the most important allergens at MGH have been stable over the past 17 years.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.325
Threshold uncertainty score0.389

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 head0.009
GPT teacher head0.226
Teacher spread0.217 · 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 designNot applicable
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

Citations10
Published2009
Admission routes1
Has abstractyes

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