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Record W4413365041 · doi:10.1080/09273948.2025.2548944

Disease of the Year 2025: Uveitis Masquerade Syndromes Neoplastic Masquerades in Adults

2025· article· en· W4413365041 on OpenAlex
Zohar Habot-Wilner, Michael Ostrovsky, Ester Carreño, Laura Domínguez García, Sofia Androudi, Piergiorgio Neri, Sarah Touhami, Inês Leal

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOcular Immunology and Inflammation · 2025
Typearticle
Languageen
FieldMedicine
TopicCNS Lymphoma Diagnosis and Treatment
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineDiseaseUveitisDermatologyPathologyOphthalmology

Abstract

fetched live from OpenAlex

Ocular neoplastic masquerade syndromes in adults pose a significant diagnostic challenge, as intraocular malignancies can closely mimic inflammatory ocular diseases. This review focuses on intraocular lymphoma, including vitreoretinal lymphoma and uveal lymphoma, and on choroidal metastases. It provides a comprehensive overview of disease epidemiology, symptoms, clinical manifestations, imaging findings, diagnostic approach, the role of ancillary testing, and current management strategies. The importance of a multidisciplinary approach is emphasized. This review aims to provide clinicians with practical tools for diagnosing and managing neoplastic masquerade syndromes.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.230

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.004
GPT teacher head0.223
Teacher spread0.218 · 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