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Record W2044544274 · doi:10.1159/000325758

Kaposi’s Sarcoma of the Thyroid Gland in an HIV-Negative Woman

2007· article· en· W2044544274 on OpenAlexaff
Anna W. Poniecka, Zeina Ghorab, David Arnold, Amr S. Khaled, Parvin Ganjei‐Azar

Bibliographic record

VenueActa Cytologica · 2007
Typearticle
Languageen
FieldMedicine
TopicViral-associated cancers and disorders
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineThyroidSarcomaHuman immunodeficiency virus (HIV)PathologyInternal medicineVirology

Abstract

fetched live from OpenAlex

BACKGROUND: Kaposi's sarcoma (KS) is a neoplastic disease that affects primarily the skin, but visceral involvement is not uncommon. Most of the cases are seen in AIDS patients and transplant recipients; however, rare HIV-negative cases have also been reported. Involvement of the thyroid is exceedingly rare, with only a fw cases reported, all of them associated with AIDS. CASE: A 45-year-old, black, Haitian woman presented with a slowly enlarging left side of the thyroid. Computed tomography showed multiple thyroid nodules, and there was no uptake of iodine on the nuclear scan. Fine needle aspiration of the lesion was performed. The smears were composed of spindle and plasmacytoid cells, which raised the possibility of medullary carcinoma. The patient underwent left hemithyroidectomy. Histologic examination showed KS in the thyroid. CONCLUSION: We present the first case of KS of the thyroid in a HIV-negative patient. Familiarity with the cytologic features can be useful in making the diagnosis.

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 score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
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 head0.017
GPT teacher head0.280
Teacher spread0.263 · 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

Citations15
Published2007
Admission routes1
Has abstractyes

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