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Record W3157994826 · doi:10.1097/iop.0000000000001986

Eyelid–Cheek Junction Soft-Tissue Perineurioma: Case Report and Controversies

2021· article· en· W3157994826 on OpenAlexaff
Lily Zhao, Faisal Jarrar, Ahsen Hussain, Martin Hyrcza, John T. Harvey

Bibliographic record

VenueOphthalmic Plastic and Reconstructive Surgery · 2021
Typearticle
Languageen
FieldMedicine
TopicNeurofibromatosis and Schwannoma Cases
Canadian institutionsUniversity of CalgaryDalhousie UniversityMcMaster University
Fundersnot available
KeywordsMedicineEyelidCheekSoft tissueDermatofibromaPathologyDifferential diagnosisLesionBiopsyAnatomyImmunohistochemistryPalpebral fissureRadiology

Abstract

fetched live from OpenAlex

Perineurioma is a rare soft-tissue tumor with characteristic histologic and immunohistochemical features. The diagnosis; however, can be met with certain challenges. A 71-year-old woman presented with an enlarging painless mass in the right lower eyelid-cheek junction. The lesion presented as a raised overhanging trunk-shaped mass. An excisional biopsy and local reconstruction were performed. The overall morphology and immunohistochemical findings were most supportive of a cellular soft-tissue perineurioma, with differential diagnoses including dermatofibroma. To the authors' knowledge, this is the first histopathologically reported case of a superficially occurring soft-tissue perineurioma in the eyelid-cheek junction. The authors discuss the presentation, relevant literature, and controversies associated with this 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)0.001
metaresearch head score (Gemma)0.005
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 score0.006
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.003
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0060.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.018
GPT teacher head0.248
Teacher spread0.230 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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