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Record W2040217009 · doi:10.14740/jmc.v6i3.2071

Uterine Leiomyosarcoma Presenting With Bilateral Orbital and Left Neck Metastases

2015· article· en· W2040217009 on OpenAlexvenueno aff
Sunil Dutt Sharma, Gaurav Kumar, Hesham Kaddour

Bibliographic record

VenueJournal of Medical Cases · 2015
Typearticle
Languageen
FieldMedicine
TopicUterine Myomas and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLeiomyosarcomaRadiation therapyRadiologySurgeryDiplopia

Abstract

fetched live from OpenAlex

Uterine leiomyosarcoma is a rare neoplasm of mesodermic origin with a predilection for hematologic dissemination, but bilateral orbital metastases have never been reported. A 63-year-old lady presented with an 18-month history of a left neck and left breast mass, and a short history of left eye pain and intermittent diplopia. Ultrasound-guided core biopsy of the left neck node showed evidence of leiomyosarcoma, and computed tomography of the orbits demonstrated bilateral infraorbital masses arising from the medial recti. The patient was diagnosed with uterine leiomyosarcoma with orbital metastases. She was treated with bilateral orbital radiotherapy but had further disease progression, and has since started doxorubicin. Surgery is usually advocated in the management of metastatic leiomyosarcoma, but given the extensive metastases in this case, radiotherapy was the preferred option. This is the first reported case of bilateral orbital and neck metastases from a uterine leimyosarcoma. J Med Cases. 2015;6(3):131-133 doi: http://dx.doi.org/10.14740/jmc2071w

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)0.001
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 score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0020.001
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 head0.042
GPT teacher head0.330
Teacher spread0.289 · 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
Published2015
Admission routes1
Has abstractyes

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