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Record W4412003093 · doi:10.1182/blood.2025029269

<i>SRSF2</i>-mutated MDS: bortezomib STAT?

2025· letter· en· W4412003093 on OpenAlexaff
Aly Karsan

Bibliographic record

VenueBlood · 2025
Typeletter
Languageen
FieldImmunology and Microbiology
TopicImmunodeficiency and Autoimmune Disorders
Canadian institutionsUniversity of British Columbia
FundersCelgeneSanofiPfizerBristol-Myers SquibbAmgen
KeywordsstatBortezomibMedicineMultiple myelomaInternal medicineBiologyGeneticsSignal transductionSTAT3

Abstract

fetched live from OpenAlex

understand the site of interaction between BCL7A and IRF4 that leads to its sequestration and inactivation uncovered by Chakraborty et al may perhaps enhance proximity-inducing therapeutic efforts or open alternative therapeutic avenues.In summary, this work elegantly describes how BCL7A downregulation "releases the brakes" on IRF4, contributing to myeloma cell "acceleration."Conflict-of-interest disclosure: C.P. has received honoraria from Celgene/Bristol Myers Squibb for advisory boards, educational talks, and participation in data monitoring boards

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)0.002
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.010
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0100.008
Insufficient payload (model declined to judge)0.0030.003

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 head0.006
GPT teacher head0.205
Teacher spread0.199 · 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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