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Record W4408190133 · doi:10.1080/24745332.2025.2455402

A Vexing diagnosis: A case report on VEXAS syndrome

2025· article· en· W4408190133 on OpenAlexaff
Lee Fidler

Bibliographic record

VenueCanadian Journal of Respiratory Critical Care and Sleep Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicOtitis Media and Relapsing Polychondritis
Canadian institutionsHealth Sciences CentreUniversity Health NetworkSunnybrook Health Science CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineComputer science

Abstract

fetched live from OpenAlex

We report a 74-year-old male with a remote history of smoking and macrocytic anemia, who developed persistent cough, dyspnea, and systemic symptoms. The constellation of fluctuating pulmonary infiltrates, pleural effusions, and hematological abnormalities ultimately led to a diagnosis of VEXAS syndrome with UBA1 mutation confirmation after initial diagnostic uncertainty. This case underscores the challenges in diagnosing VEXAS due to its rarity and multisystem involvement and highlights the pulmonary manifestations seen in patients with this syndrome. Raising awareness regarding the existence of VEXAS and the need for genetic testing and multidisciplinary involvement is crucial to improving disease recognition and outcomes in this condition.

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 score0.007
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0030.002
Scholarly communication0.0020.003
Open science0.0020.003
Research integrity0.0070.005
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 head0.022
GPT teacher head0.320
Teacher spread0.298 · 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
Published2025
Admission routes1
Has abstractyes

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