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Record W3168405083 · doi:10.1016/j.jcyt.2021.04.009

Consensus International Council for Commonality in Blood Banking Automation–International Society for Cell & Gene Therapy statement on standard nomenclature abbreviations for the tissue of origin of mesenchymal stromal cells

2021· article· en· W3168405083 on OpenAlexaff
Sowmya Viswanathan, Rachele Ciccocioppo, Jacques Galipeau, Mauro Krampera, Katarina Le Blanc, Iván Martín, Karen Moniz, Jan A. Nolta, Donald G. Phinney, Yufang Shi, Zbigniew M. Szczepiorkowski, Karin Tarte, Daniel J. Weiss, Paul Ashford

Bibliographic record

VenueCytotherapy · 2021
Typearticle
Languageen
FieldMedicine
TopicMesenchymal stem cell research
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersInstitut des Sciences du Cerveau de Toulouse
KeywordsMesenchymal stem cellCell therapyMedicineTerminologyRegenerative medicineBioinformaticsBiologyImmunologyPathologyStem cellCell biology

Abstract

fetched live from OpenAlex

The Cellular Therapy Coding and Labeling Advisory Group of the International Council for Commonality in Blood Banking Automation and the International Society for Cell & Gene Therapy mesenchymal stromal cell (MSC) committee are providing specific recommendations on abbreviating tissue sources of culture-adapted MSCs. These recommendations include using abbreviations based on the ISBT 128 terminology model that specifies standard class names to distinguish cell types and tissue sources for culture-adapted MSCs. Thus, MSCs from bone marrow are MSC(M), MSCs from cord blood are MSC(CB), MSCs from adipose tissue are MSC(AT) and MSCs from Wharton's jelly are MSC(WJ). Additional recommendations include using these abbreviations through the full spectrum of pre-clinical, translational and clinical research for the development of culture-adapted MSC products. This does not apply to basic research focused on investigating the developmental origins, identity or functionalities of endogenous progenitor cells in different tissues. These recommendations will serve to harmonize nomenclature in describing research and development surrounding culture-adapted MSCs, many of which are destined for clinical and/or commercial translation. These recommendations will also serve to align research and development efforts on culture-adapted MSCs with other cell therapy products.

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)0.084
metaresearch head score (Gemma)0.082
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: Other · Consensus signal: Other
Teacher disagreement score0.084
Threshold uncertainty score0.445

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0840.082
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0070.006
Science and technology studies0.0050.006
Scholarly communication0.0120.005
Open science0.0090.006
Research integrity0.0160.019
Insufficient payload (model declined to judge)0.0190.028

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 head0.150
GPT teacher head0.379
Teacher spread0.229 · 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
GenreOther

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

Citations31
Published2021
Admission routes1
Has abstractyes

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