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Record W4389438361 · doi:10.1097/dad.0000000000002591

Primary Mucinous Carcinoma of Skin: A Rare Cutaneous Neoplasm. Clinicopathologic Features, Differential Diagnoses, and Review of Literature

2023· article· en· W4389438361 on OpenAlexaff
Mukund Tinguria

Bibliographic record

VenueAmerican Journal of Dermatopathology · 2023
Typearticle
Languageen
FieldMedicine
TopicCancer and Skin Lesions
Canadian institutionsBrantford Energy (Canada)
Fundersnot available
KeywordsPathologyMedicineMucinous carcinomaDifferential diagnosisAdenocarcinomaMalignancyHistopathologyMyoepithelial cellImmunohistochemistryCancerInternal medicine

Abstract

fetched live from OpenAlex

ABSTRACT: Primary mucinous carcinoma of the skin (PMCS) is a rare malignant neoplasm of sweat gland origin, with an incidence of 0.07 per million. Histologically, it may be difficult to differentiate it from metastatic mucinous carcinomas of the skin. A case of PMCS is reported here in a 59-year-old woman who presented with a lesion on the right lower eyelid. Histological examination revealed features of mucinous adenocarcinoma. The main differential diagnosis was metastatic mucinous adenocarcinoma; however, the lack of colorectal and lung markers and the presence of focal in situ components were consistent with the diagnosis of PMCS. PMCS and breast mucinous carcinoma share immunohistochemical markers, such as GCDFP-15 and mammaglobin; however, focal in situ component with the presence of myoepithelial cells in the tumor ruled out metastatic mucinous carcinoma of breast origin. The subsequent mammograms did not reveal any breast lesions. Colonoscopy did not show any evidence of colonic malignancy, and imaging studies (CT scan) did not show any evidence of neoplasm in the body. These findings were in keeping with a diagnosis of PMCS. The present case emphasizes the importance of clinicopathological correlation, histopathology, and immunohistochemistry in the accurate diagnosis of PMCS and summarizes the literature on these rare cutaneous neoplasms.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.309
Threshold uncertainty score0.653

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.276
Teacher spread0.269 · 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

Citations9
Published2023
Admission routes1
Has abstractyes

Explore more

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