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Record W2030349189 · doi:10.14740/jmc.v5i6.1599

A 47-Year-Old Man With Rosai-Dorfman Disease

2014· article· en· W2030349189 on OpenAlexvenueno aff
Sara Pereira, Liliana Oliveira, Joana Barros, Hugo Silva, Carla Melo, Jorge Salomão, Augusto Duarte

Bibliographic record

VenueJournal of Medical Cases · 2014
Typearticle
Languageen
FieldMedicine
TopicHistiocytic Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsEmperipolesisRosai–Dorfman diseaseMedicineCD68EtiologyHistiocytosisLymphPathologyBiopsyDermatologyDiseaseImmunohistochemistry

Abstract

fetched live from OpenAlex

Rosai-Dorfman is a rare and benign disease with unknown etiology, characterized by histiocytosis and emperipolesis, generally associated with lymphadenopathy. It is mainly observed in Caucasians and African children and young adults. A 47-year-old man, Caucasian, with a personal history of chronic alcoholism presented with two lymph nodes with progressive growth over a period of 6 months, one located in the pre-auricular region with 2 cm and another in the sub-mandibular region with 3 cm. Clinical examination showed two discrete, non-tender, painless and immobile nodes. Biopsy of the nodes was performed. Emperipolesis and cells expressing positive immunoreactivity for protein S-100, CD1a and CD68 were observed making the diagnosis of Rosai-Dorfman disease (RDD). RDD is a benign pathology, self-limited and no special treatment is needed in most cases. J Med Cases. 2014;5(6):347-350 doi: http://dx.doi.org/ 10.14740 /jmc1599w

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.013
GPT teacher head0.284
Teacher spread0.271 · 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
Published2014
Admission routes1
Has abstractyes

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