MétaCan
Menu
Back to cohort
Record W4391718044 · doi:10.1016/j.eclinm.2024.102476

Innovative cellular therapies for autoimmune diseases: expert-based position statement and clinical practice recommendations from the EBMT practice harmonization and guidelines committee

2024· article· en· W4391718044 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEClinicalMedicine · 2024
Typearticle
Languageen
FieldMedicine
TopicCAR-T cell therapy research
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicinePosition paperPosition statementIntensive care medicineImmunosuppressionBest practiceHarmonizationImmunologyFamily medicinePathology

Abstract

fetched live from OpenAlex

Autoimmune diseases (ADs) are characterized by loss of immune tolerance, high chronicity, with substantial morbidity and mortality, despite conventional immunosuppression (IS) or targeted disease modifying therapies (DMTs), which usually require repeated administration. Recently, novel cellular therapies (CT), including mesenchymal stromal cells (MSC), Chimeric Antigen Receptors T cells (CART) and regulatory T cells (Tregs), have been successfully adopted in ADs. An international expert panel of the European Society for Blood and Marrow Transplantation and the International Society for the Cell and Gene Therapy, reviewed all available evidence, based on the current literature and expert practices, on use of MSC, CART and Tregs, in AD patients with rheumatological, neurological, and gastroenterological indications. Expert-based consensus and recommendations for best practice and quality of patient care were developed to support clinicians, scientists, and their multidisciplinary teams, as well as patients and care providers and will be regularly updated.

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.

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)0.005
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.663
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.125
GPT teacher head0.495
Teacher spread0.370 · 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