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Record W4309366412 · doi:10.1111/cup.14361

<scp>PRAME</scp> immunohistochemistry is useful in differentiating oral melanomas from nevi and melanotic macules

2022· article· en· W4309366412 on OpenAlexaff
Toby Schmitt, Jonathan Cassolato Lee, Magdalena Martinka, Yen Chen Kevin Ko

Bibliographic record

VenueJournal of Cutaneous Pathology · 2022
Typearticle
Languageen
FieldMedicine
TopicCutaneous Melanoma Detection and Management
Canadian institutionsVancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineMelanomaDermatologyOral cavityPathologyImmunohistochemistryStainingHMB-45Cancer researchDentistry

Abstract

fetched live from OpenAlex

BACKGROUND: Oral melanocytic neoplasms pose a diagnostic challenge to pathologists owing to their rarity relative to those in the skin. The utility of PRAME in distinguishing nevi from melanomas has been established in the skin, but limited information exists regarding its usefulness in the oral cavity. METHODS: Thirty-five previously diagnosed pigmented oral lesions were retrospectively evaluated with PRAME. The lesions consisted of 16 oral nevi, 10 melanomas, and 10 melanotic macules. RESULTS: Strong and diffuse nuclear PRAME staining was observed in all but one of the oral melanomas, which showed no staining. No nuclear PRAME staining was observed in any of the oral nevi or melanotic macules. CONCLUSIONS: PRAME is a useful tool in the evaluation of oral melanocytic neoplasms. Our data indicate that PRAME is a highly specific but incompletely sensitive marker of oral melanoma. Larger studies could further illuminate the diagnostic value of PRAME in oral lesions.

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: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.605
Threshold uncertainty score0.835

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
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 head0.012
GPT teacher head0.250
Teacher spread0.239 · 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

Citations7
Published2022
Admission routes1
Has abstractyes

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