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Record W3187155906 · doi:10.3324/haematol.2021.279232

Daratumumab, an original approach for treating multi-refractory autoimmune cytopenia

2021· article· en· W3187155906 on OpenAlexaff
Étienne Crickx, Sylvain Audia, A. Robbins, David Boutboul, Thibault Comont, Morgane Cheminant, Éric Oksenhendler, Bertrand Godeau, Marc Michel, Matthieu Mahévas

Bibliographic record

VenueHaematologica · 2021
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsHôpital Saint-François d'Assise
Fundersnot available
KeywordsDaratumumabCytopeniaMedicineRefractory (planetary science)OncologyDermatologyInternal medicineLenalidomideMultiple myelomaBiologyBone marrow

Abstract

fetched live from OpenAlex

Daratumumab, an original approach for treating multi-refractory autoimmune cytopenia Immune thrombocytopenia (ITP) and warm autoimmune hemolytic anemia (AIHA) are antibody-mediated autoimmune diseases in which plasma cells secrete pathogenic antibodies directed against platelet and red blood cell antigens. 1 Some patients show no response to first-or second-line treatments, including corticosteroids, rituximab, immunosuppressive drugs, splenectomy and, in the case of ITP, thrombopoietin receptor agonists, a situation that increases the risk of morbidity and mortality. In these refractory cases, persistent autoreactive long-lived plasma cells in the bone marrow could explain treatment failure.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.247
Threshold uncertainty score0.625

Codex and Gemma teacher scores by category

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

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 head0.054
GPT teacher head0.327
Teacher spread0.273 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations50
Published2021
Admission routes1
Has abstractyes

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