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Record W2342059280 · doi:10.14785/lymphosign-2016-0002

Paradoxical hyperhidrosis in a patient with ectodermal dysplasia and immunodeficiency

2016· article· en· W2342059280 on OpenAlexaffvenue
Amiirah Aujnarain, Catherine T. Chung, Julia Upton

Bibliographic record

VenueLymphoSign Journal · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNF-κB Signaling Pathways
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsEctodermal dysplasiaSWEATHyperhidrosisDermatologyImmunodeficiencySkin biopsyBiopsyMedicinePhenotypePathologyBiologyInternal medicineImmunologyGeneticsImmune systemGene

Abstract

fetched live from OpenAlex

Anhidrotic Ectodermal Dysplasia with Immunodeficiency (EDA-ID) is a pleotropic disorder characterized by dental abnormalities, eccrine sweat dysgenesis, specific facies, fine sparse hair, pale wrinkled skin, and variable immune defects. The condition is caused by hypomorphic mutations (NF) κB Essential modifier protein (NEMO) gene. The clinical phenotype between patients is heterogenous and variable. Here we report a patient with a known NEMO mutation presenting with clinical features consistent with EDA-ID, except for paradoxical hyperhidrosis despite having a biopsy-proven reduced number of sweat glands. Statement of novelty: We report a patient with X-linked EDA-ID due to NEMO deficiency who presented with marked diaphoresis despite biopsy-proven reduced sweat glands and ectodermal dysplasia.

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: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

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 studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0020.001
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 head0.005
GPT teacher head0.188
Teacher spread0.184 · 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

Citations1
Published2016
Admission routes2
Has abstractyes

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