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Record W4401382529 · doi:10.1056/nejmc2407381

Studies of Exagamglogene Autotemcel — Age and Place

2024· letter· en· W4401382529 on OpenAlexaboutno aff
Haydar Frangoul

Bibliographic record

VenueNew England Journal of Medicine · 2024
Typeletter
Languageen
FieldPhysics and Astronomy
TopicOrigins and Evolution of Life
Canadian institutionsnot available
Fundersnot available
KeywordsAging in placeMedicineGerontology

Abstract

fetched live from OpenAlex

To the Editor: Generally, we should be cautious about gene therapy and gene-editing–based therapy until long-term follow-up results are available. However, data from the recent studies of exagamglogene autotemcel (exa-cel) in the treatment of β-thalassemia (CLIMB THAL-111) by Locatelli et al. 1 and in the treatment of sickle cell disease (CLIMB SCD-121) by Frangoul et al. 2 (both in the May 9 issue) support the safety of this experimental cell therapy, and thus more patients may now be eligible for it. These studies included patients 12 to 35 of age who were recruited from Canada, the United Kingdom, the United States, and . . .

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)0.004
metaresearch head score (Gemma)0.022
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.021
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0210.019
Insufficient payload (model declined to judge)0.0030.002

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 head0.035
GPT teacher head0.304
Teacher spread0.270 · 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
GenreEditorial

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

Citations0
Published2024
Admission routes1
Has abstractyes

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