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Record W1983150941 · doi:10.4061/2011/498132

From Banking to International Governance: Fostering Innovation in Stem Cell Research

2011· article· en· W1983150941 on OpenAlexafffund
Rosario Isasi, Bartha Maria Knoppers

Bibliographic record

VenueStem Cells International · 2011
Typearticle
Languageen
FieldMedicine
TopicBiomedical Ethics and Regulation
Canadian institutionsMcGill University
FundersCanadian Institutes of Health ResearchStem Cell Network
KeywordsStem cellCorporate governanceBusinessTranslational researchBiotechnologyBiologyCell biologyFinance

Abstract

fetched live from OpenAlex

Stem cell banks are increasingly recognized as an essential resource of biological materials for both basic and translational stem cell research. By providing transnational access to quality controlled and ethically sourced stem cell lines, stem cell banks seek to foster international collaboration and innovation. However, given that national stem cell banks operate under different policy, regulatory and commercial frameworks, the transnational sharing of stem cell materials and data can be complicating. This paper will provide an overview of the most pressing challenges regarding the governance of stem cell banks, and the difficulties in designing regulatory and commercial frameworks that foster stem cell research. Moreover, the paper will shed light on the numerous international initiatives that have arisen to help harmonize and standardize stem cell banking and research processes to overcome such challenges.

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)0.061
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.061
Threshold uncertainty score0.324

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0610.048
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0060.031
Scholarly communication0.0180.014
Open science0.0010.017
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0040.001

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 head0.153
GPT teacher head0.370
Teacher spread0.217 · 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 designTheoretical or conceptual
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

Citations24
Published2011
Admission routes2
Has abstractyes

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