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Record W2799837647 · doi:10.5430/jst.v8n2p7

Cytological diagnosis of metastatic melanoma presenting as an isolated pleural effusion: A case report

2018· article· en· W2799837647 on OpenAlexvenueno aff
Konstantinos Kosmas, Anna Tsonou, Georgia Mitropoulou, Anastasia Mandilara, Olga Papadopoulou, Eufrosyni Salemi

Bibliographic record

VenueJournal of Solid Tumors · 2018
Typearticle
Languageen
FieldMedicine
TopicCutaneous Melanoma Detection and Management
Canadian institutionsnot available
Fundersnot available
KeywordsPathologyEosinophilicMedicineMelanomaMetastasisPleural effusionContext (archaeology)Epithelioid cellCytologyGiant cellImmunohistochemistryCancerBiologyCancer researchRadiologyInternal medicine

Abstract

fetched live from OpenAlex

Malignant melanoma (MM) is a malignant melanocytic neoplasm that occurs mainly in the skin but it can also involve any tissue. It has the capacity to metastasize widely and quickly to various sites without any intermediate stops, sometimes many years after treatment of the primary tumor. It is almost impossible to predict which organ system will be invaded by melanoma from a given primary site. We report the cytomorphologic and immunocytochemical findings of a male patient with isolated pleural metastasis of MM without pulmonary parenchymal metastatic involvement after 10 years of progression-free survival. Pleural fluid cytology revealed epithelioid cells of variable sizes and configuration isolated or in clusters with abnormal hyperchromatic nuclei, irregularly-shaped nucleoli, abundant eosinophilic cytoplasm, multinucleated giant cells, intranuclear cytoplamic inclusions as well as many cytoplasmic melanin pigmented tumor cells. Immunocytochemical markers for melanoma HMB-45 and S-100 were positive. Metastasis of MM to pleural fluid is rare and diagnosing the disease by cytology is challenging and requires medical expertise as well as knowledge of clinical context and immunocytochemical staining evaluation.

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)0.001
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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.837

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0010.000

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 head0.031
GPT teacher head0.328
Teacher spread0.297 · 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 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
Published2018
Admission routes1
Has abstractyes

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