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Record W4414249926 · doi:10.1111/hae.70128

The Critical Need to Consolidate All Gene Therapy Data in Haemophilia

2025· letter· en· W4414249926 on OpenAlexaff
Barbara A. Konkle, Donna Coffin, Cédric Hermans, M. Naccache, Brian O’Mahony, Glenn F. Pierce

Bibliographic record

VenueHaemophilia · 2025
Typeletter
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsCanadian Hemophilia Society
Fundersnot available
KeywordsHaemophiliaClinical trialGenetic enhancementDosingHaemophilia AHaemophilia BMilestoneTargeted therapy

Abstract

fetched live from OpenAlex

To the Editor: Gene therapy for haemophilia has been in development for several decades, with the first clinical attempts initiated in the 1990s. These early studies, including six initial trials, laid the foundation for subsequent systemic liver-directed adeno-associated virus (AAV) trials that ultimately led to regulatory approvals. A pivotal milestone came in 2011 with the publication by Nathwani et al., which demonstrated the first successful systemic AAV8-FIX gene therapy for haemophilia B, achieving sustained therapeutic factor IX levels with immune modulation using prednisolone. [...]

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)0.046
metaresearch head score (Gemma)0.097
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: Commentary · Consensus signal: none
Teacher disagreement score0.046
Threshold uncertainty score0.244

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0460.097
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0050.004
Science and technology studies0.0020.006
Scholarly communication0.0140.025
Open science0.0040.007
Research integrity0.0120.024
Insufficient payload (model declined to judge)0.0230.010

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 head0.106
GPT teacher head0.395
Teacher spread0.289 · 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
GenreCommentary

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
Published2025
Admission routes1
Has abstractyes

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