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Record W2113117515 · doi:10.2310/7750.2010.09047

Progressive Mucinous Histiocytosis: Importance of Electron Microscopy to Confirm Diagnosis

2010· article· en· W2113117515 on OpenAlexaff
Iman Hemmati, Wendy McLeod, Richard I. Crawford

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2010
Typearticle
Languageen
FieldMedicine
TopicHistiocytic Disorders and Treatments
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicinePathologyHistiocytosisElectron microscopeDisease

Abstract

fetched live from OpenAlex

BACKGROUND: Progressive mucinous histiocytosis (PMH) is a benign, non-Langerhans cell histiocytosis with characteristic ultrastructural features that can be used for diagnosis. Once an important tool in dermatologic diagnosis, electron microscopy has been largely replaced by immunohistochemistry and immunofluorescence techniques today. However, electron microscopy occasionally still plays a crucial role in the diagnosis of dermatologic conditions. We report a case of PMH as an example of a dermatologic disorder that requires electron microscopy for its diagnosis. METHODS: A 60-year-old woman presented to our clinic with a history of small, sharply demarcated, skin-colored papules ranging from 2 to 5 mm in diameter distributed over the arms, forearms, and dorsal hands. The results of light microscopy, immunohistochemical studies, and clinical examination were inconclusive. Another biopsy for electron microscopy showed the characteristic features of PMH. CONCLUSION: This case demonstrates that a dermatopathology service still needs to have access to electron microscopy for diagnostic purposes to successfully diagnose a small number of rare conditions.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.698
Threshold uncertainty score0.511

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.014
GPT teacher head0.308
Teacher spread0.293 · 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 designObservational
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

Citations2
Published2010
Admission routes1
Has abstractyes

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