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Record W1886526654 · doi:10.4081/rt.2015.5698

Amelanotic Melanoma Presenting with Plasmacytoid Morphology and <i>BRAF V600</i> Mutation

2015· article· en· W1886526654 on OpenAlexaff
Linda Kocovski, Anita Bane, Shangguo Tang, Samih Salama, Salem Alowami

Bibliographic record

VenueRare Tumors · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMelanoma and MAPK Pathways
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineMelanomaPathologyAmelanotic melanomaMalignancyVimentinPlasmacytoid dendritic cellImmunohistochemistryEosinophilicDifferential diagnosisDabrafenibHMB-45Cancer researchMetastatic melanomaAntigenImmunologyVemurafenib

Abstract

fetched live from OpenAlex

Plasmacytoid melanoma is an unusual variant of malignant melanoma. The plasmacytoid morphology can be found in a variety of other malignancies including carcinomas, plasma cell neoplasms, lymphoproliferative disorders, and sarcomas. The authors report a rare case of plasmacytoid amelanotic malignant melanoma in a 78-year-old man presenting with an enlarging palpable, erythematous mass on his left posterior shoulder. A fine needle aspirate showed atypical findings with single amelanotic cells with high nuclear to cytoplasmic ratio, mono- and multi-nucleation with prominent nucleoli and intranuclear inclusions. Review of the excision and immunohistochemical analysis revealed the malignant plasmacytoid cells stained with vimentin, S-100, HMB-45, and other staining patterns consistent with melanoma. Initial evaluation was negative for other sites of disease. However, 4 months later, the patient was noted to have metastatic disease to his lungs and liver. Given that the tumor was noted to be BRAF V600R mutated, the patient was started on single agent dabrafenib. The plasmacytoid morphology can be found in a variety of malignancies. Melanoma should be considered in the differential diagnosis of any malignancy presenting with plasmacytoid features.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.292
Threshold uncertainty score0.539

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.013
GPT teacher head0.221
Teacher spread0.207 · 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 designBench or experimental
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

Citations7
Published2015
Admission routes1
Has abstractyes

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