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Record W4411932984 · doi:10.1038/s41584-025-01272-3

CAR T cell therapy for children with rheumatic disease: the time is now

2025· review· en· W4411932984 on OpenAlexaff
Holly Wobma, Stacy P. Ardoin, Challice L. Bonifant, Jennifer C. Cooper, Hanna Kim, Rebecca E. Sadun, Laura B. Lewandowski, Michael Keller, Robert A. Colbert, Cuoghi Edens, Kimberly DeQuattro, Kyla Driest, Julia Shalen, Ivana Stojkic, Andrea Knight, Colleen Annesley, Kathryn S. Torok, Caitlin W. Elgarten, Toshihiro Onishi, Shaun W. Jackson, Susan E. Prockop, Nirali N. Shah, Kaveh Ardalan, Margaret Lamb

Bibliographic record

VenueNature Reviews Rheumatology · 2025
Typereview
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of Health
KeywordsMedicineRheumatic diseaseDiseaseMEDLINECell therapyIntensive care medicinePediatricsCellInternal medicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.002

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 head0.359
Teacher spread0.338 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations10
Published2025
Admission routes1
Has abstractno

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