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Record W4414061569 · doi:10.70962/jhi.20250131

Treatment of severe refractory immune neutropenia with ruxolitinib: Two cases

2025· article· en· W4414061569 on OpenAlexafffund
Richard Schwarzkopf, A Chen, Stephanie Quon, Julia Varghese, Janet Roberts, Richard K. Wood, Luke Y. C. Chen

Bibliographic record

VenueJournal of Human Immunity · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBlood disorders and treatments
Canadian institutionsUniversity of British ColumbiaDalhousie University
FundersRecordati Rare DiseasesNova Scotia Health Research FoundationVGH and UBC Hospital FoundationPfizer
KeywordsNeutropeniaRefractory (planetary science)Immune systemRuxolitinibLymphocyteImmunopathology

Abstract

fetched live from OpenAlex

Two adult patients with severe immune neutropenia refractory to standard therapies achieved durable remission following treatment with the JAK inhibitor ruxolitinib. This report highlights the potential of JAK-STAT pathway inhibition for managing G-CSF and steroid-refractory immune-mediated neutropenia.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.008
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0080.004
Insufficient payload (model declined to judge)0.0010.001

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 head0.013
GPT teacher head0.292
Teacher spread0.279 · 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
Published2025
Admission routes2
Has abstractyes

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