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Record W4293056458 · doi:10.1177/01455613221119067

A Case of Unilateral Proptosis Secondary to Prostatic Metastasis

2022· article· en· W4293056458 on OpenAlexaff
Jennifer A. Silver, Hamad Almhanedi, Jonathan Lai, Alex C. Tham, Oluyomi Ajise, Marc A. Tewfik

Bibliographic record

VenueEar Nose & Throat Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicCancer Diagnosis and Treatment
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsMedicineDifferential diagnosisMetastasisAnosmiaOrbit (dynamics)Paranasal sinusesPresentation (obstetrics)Sinus (botany)RadiologyrhinorrheaBiopsySurgeryCancerDiseasePathologyInfectious disease (medical specialty)Internal medicine

Abstract

fetched live from OpenAlex

Prostate cancer metastases involving the orbit and/or paranasal sinuses represent a rare oncological presentation. Patients can have a myriad of symptoms such as proptosis, periorbital swelling, blurry vision, rhinorrhea, epistaxis, anosmia, or others depending on the structures involved. The differential diagnosis of paranasal sinus masses on imaging studies is broad and can include inflammatory, congenital, or neoplastic masses; leading to the requirement of biopsy for definitive diagnosis. Tissue sample is usually obtained via an endoscopic approach. The prognosis of such a presentation is not well described in the literature, but it is usually guarded due to the advanced stage of the disease and generally a poorly differentiated primary tumor. Treatments usually aim to reduce the burden of disease and debulk the tumor mass for palliative purposes. We present a case of a 71-year-old male presenting with unilateral proptosis and periorbital swelling secondary to prostatic metastasis.

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 score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.002
Science and technology studies0.0030.002
Scholarly communication0.0020.003
Open science0.0010.003
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.026
GPT teacher head0.302
Teacher spread0.276 · 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
Published2022
Admission routes1
Has abstractyes

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