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Record W3186180673 · doi:10.1177/10668969211035059

Benign Metastasizing Leiomyoma in the Lung Presenting in a Phyllodes-Like Pattern Mimicking a Biphasic Tumor: A Case Report

2021· article· en· W3186180673 on OpenAlexaff
Saleh Fadel, Patrick J. Villeneuve, Ashish Gupta, Sarah Strickland, Marcio M. Gomes

Bibliographic record

VenueInternational Journal of Surgical Pathology · 2021
Typearticle
Languageen
FieldMedicine
TopicSoft tissue tumor case studies
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsLungPathologyMedicineDifferential diagnosisLeiomyomaImmunohistochemistryPhyllodes tumorS100 proteinRadiologyInternal medicine

Abstract

fetched live from OpenAlex

Primary biphasic tumors of the lung are rare. Lung lesions with a biphasic pattern are far more commonly primary or metastatic soft tissue tumors with entrapped native respiratory epithelium, giving the false impression of a biphasic tumor. We report a case of bilateral benign metastasizing leiomyomas in a 69-year-old female where the tumor cells diffusely entrapped native respiratory glands in a phyllodes-like pattern. The radiographic characteristics and histologic appearance were not immediately diagnostic and covered a wide differential. Reaching the final diagnosis required the use of immunohistochemical studies as well as correlation with the patient's history and radiographic findings. To the best of our knowledge, this is the first report of pulmonary benign metastasizing leiomyoma presenting in a phyllodes-like pattern. This case illustrates the importance of considering entrapment of native lung epithelium in the differential diagnosis of biphasic-appearing lung tumors.

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)0.000
metaresearch head score (Gemma)0.003
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.034
GPT teacher head0.350
Teacher spread0.316 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

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