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Record W2054274928 · doi:10.1159/000356229

A Classic Clinical Case: Neutrophilic Eccrine Hidradenitis

2013· article· en· W2054274928 on OpenAlexaff
Ana Maria Copaescu, Jean‐François Castilloux, Myrna Chababi‐Atallah, Christian Sinave, Janie Bertrand

Bibliographic record

VenueCase Reports in Dermatology · 2013
Typearticle
Languageen
FieldMedicine
TopicChemotherapy-related skin toxicity
Canadian institutionsCentre Hospitalier Universitaire de SherbrookeUniversité de Sherbrooke
Fundersnot available
KeywordsMedicineDifferential diagnosisDermatologyCellulitisPresentation (obstetrics)Internal medicineSurgeryPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Neutrophilic eccrine hidradenitis (NEH) is a rare condition described mostly in adult patients receiving chemotherapy for acute myelogenous leukemia. When it affects the facial region, it can mimic cellulitis and delay the diagnostic, thus proper recognition is essential. OBJECTIVE: This article describes a classic case of NEH. We will review the diagnostic, the differential diagnostic (mostly cellulitis) and the management of this condition. METHODS: After a literature review, the patient's file was properly studied in order to portray a clear picture of this condition. Medical photographs and appropriate physical examination upon presentation are also included. RESULTS: The diagnostic for NEH was suggested by the clinical presentation and confirmed histopathologically (skin biopsy). CONCLUSION: The diagnostic of NEH is essential in order to prevent multiple unnecessary antibiotics.

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)0.002
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: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.028
GPT teacher head0.333
Teacher spread0.305 · 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

Citations24
Published2013
Admission routes1
Has abstractyes

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