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Record W4308769675 · doi:10.1017/cjn.2022.321

IgG4-Related Disease of the Central Nervous System: A Case Series

2022· article· en· W4308769675 on OpenAlexaffvenueabout
Ghada Abbas, Jason Karamchandani, Anthony Ciarallo, Liam Durcan

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2022
Typearticle
Languageen
FieldMedicine
TopicIgG4-Related and Inflammatory Diseases
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsMedicineGold standard (test)DiseaseIgG4-related diseasePediatricsRadiologyMagnetic resonance imagingPathology

Abstract

fetched live from OpenAlex

IgG4-related disease (IgG4-RD) is a rare and often misdiagnosed disorder with limited literature that highlights the different neurological presentations of this treatable disease. The diagnosis of IgG4-RD could be challenging, while imaging is fundamental for the diagnosis, biopsy is considered the gold standard. Most cases respond well to steroids and immunosuppressive therapy. This is a case series study that illustrates the varied neurological presentations of IgG4-RD through three different patients that were followed at the Montreal Neurological Institute. This paper takes you through the diagnostic strategy that we followed to accurately diagnose and treat those patients.

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.538
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0050.006
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.231
Teacher spread0.213 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations5
Published2022
Admission routes3
Has abstractyes

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Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences NeurologiquesSame topicIgG4-Related and Inflammatory DiseasesFrench-language works237,207