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Record W4210446598 · doi:10.1111/cup.14205

The distinctive histopathology of cicatricial alopecia caused by <scp>IgG4</scp>‐related disease

2022· article· en· W4210446598 on OpenAlexaff
Leonard C. Sperling, Ken von Kuster, Shane Silver

Bibliographic record

VenueJournal of Cutaneous Pathology · 2022
Typearticle
Languageen
FieldMedicine
TopicIgG4-Related and Inflammatory Diseases
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPathologyHistopathologyMedicineHistiocyteFibrosisScarring alopeciaDermatologyScalp

Abstract

fetched live from OpenAlex

IgG4-related disease (IgG4-RD) is characterized by masses at multiple sites, a dense lymphoplasmacytic infiltrate containing numerous IgG4+ plasma cells, storiform fibrosis, and often elevated serum IgG4 concentrations. We present a third case of alopecia (in this instance, cicatricial) caused by IgG4-RD. Based on our findings combined with those seen in two other cases, the histopathologic features of IgG4-RD alopecia include: sparing of the epidermis, cicatricial (scarring) alopecia with a markedly decreased number of hairs, miniaturization of residual hairs, and total loss of the sebaceous glands. Groups of follicles with their associated sebaceous glands (follicular units) are replaced by an extremely dense infiltrate of lymphocytes and especially plasma cells. Histiocytic aggregates, both foamy and non-foamy, may also be present. Variable degrees of fibroplasia may be present but are not an important feature in this type of alopecia.

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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.005
GPT teacher head0.223
Teacher spread0.218 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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