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Record W4386636748 · doi:10.1016/j.stemcr.2023.08.003

ISSCR standards for the use of human stem cells in basic research

2023· review· en· W4386636748 on OpenAlexafffund
Tenneille E. Ludwig, Peter W. Andrews, Ivana Barbaric, Nissim Benvenisty, Anita Bhattacharyya, Jeremy M. Crook, Laurence Dahéron, Jonathan S. Draper, Lyn Healy, Meritxell Huch, Maneesha S. Inamdar, Kim B. Jensen, Armin Kurtz, Madeline A. Lancaster, Prisca Liberali, Matthias P. Lütolf, Christine L. Mummery, Martín F. Pera, Yoji Sato, Noriko Shimasaki, Austin Smith, Jihwan Song, Claudia Spits, Christine A. Wells, Tongbiao Zhao, Jack T. Mosher

Bibliographic record

VenueStem Cell Reports · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsStem Cell Network
FundersEuropean Research CouncilMedical Research CouncilTohoku UniversityMinistry of Health and WelfareMinistry of Science, ICT and Future PlanningEngineering Research CentersKanagawa Institute of Industrial Science and TechnologyNagoya City UniversityWistar InstituteUK Regenerative Medicine PlatformUniversity of TokyoSimons Foundation Autism Research InitiativeSimons FoundationBurroughs Wellcome FundNational Research Foundation of KoreaMassachusetts Department of Agricultural ResourcesFaculty of Pharmacy and Pharmaceutical Sciences, University of AlbertaWisconsin Alumni Research FoundationFrancis Crick InstituteWellcome TrustNovo Nordisk FondenCancer Research UKDoris Duke Charitable Foundation
KeywordsStem cellBiologyInduced pluripotent stem cellBiotechnologyBasic researchRisk analysis (engineering)Engineering ethicsBiochemical engineeringData scienceComputer scienceBusinessLibrary scienceCell biologyEmbryonic stem cellEngineering

Abstract

fetched live from OpenAlex

The laboratory culture of human stem cells seeks to capture a cellular state as an in vitro surrogate of a biological system. For the results and outputs from this research to be accurate, meaningful, and durable, standards that ensure reproducibility and reliability of the data should be applied. Although such standards have been previously proposed for repositories and distribution centers, no widely accepted best practices exist for laboratory research with human pluripotent and tissue stem cells. To fill that void, the International Society for Stem Cell Research has developed a set of recommendations, including reporting criteria, for scientists in basic research laboratories. These criteria are designed to be technically and financially feasible and, when implemented, enhance the reproducibility and rigor of stem cell research.

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)0.027
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.973
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.019
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0080.008
Science and technology studies0.0020.005
Scholarly communication0.0040.004
Open science0.0060.004
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0080.013

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 head0.220
GPT teacher head0.425
Teacher spread0.205 · 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.

Study designNot applicable
DomainMethods
GenreReview

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

Citations104
Published2023
Admission routes2
Has abstractyes

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