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Record W2175157537 · doi:10.7205/milmed.173.2.217

Successful Treatment of Disabling Cholinergic Urticaria

2008· article· en· W2175157537 on OpenAlexaff
Jeff H. Feinberg, Charles B. Toner

Bibliographic record

VenueMilitary Medicine · 2008
Typearticle
Languageen
FieldMedicine
TopicUrticaria and Related Conditions
Canadian institutionsBell Helicopter Textron (Canada)
Fundersnot available
KeywordsMedicineCetirizineRashDermatologyAnesthesia

Abstract

fetched live from OpenAlex

A 22-year-old African American U.S. sailor presented with an intermittent pruritic eruption precipitated by mild activity for the last 2 years. She developed an extremely pruritic papular rash that would quickly coalesce into larger wheals following any exercise, light activity such as vacuuming, or taking hot showers. This condition had been getting progressively worse, preventing her from successfully completing her physical readiness test and other required physical training for the last 2 years. Previous treatment with antihistamines and steroids had failed to control her symptoms. She was diagnosed with cholinergic urticaria, successfully controlled with a combination of cetirizine, montelukast, and propanolol. She has since been returned to full military duty and is able to exercise regularly.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.289
Teacher spread0.258 · 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 designCase report
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

Citations31
Published2008
Admission routes1
Has abstractyes

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