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Record W2138848591 · doi:10.5966/sctm.2013-0099

The DISCUSS Project: Induced Pluripotent Stem Cell Lines From Previously Collected Research Biospecimens and Informed Consent: Points to Consider

2013· article· en· W2138848591 on OpenAlexaff
Geoffrey Lomax, Sara Chandros Hull, Justin Lowenthal, Mahendra S. Rao, Rosario Isasi

Bibliographic record

VenueStem Cells Translational Medicine · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsMcGill University
FundersU.S. Public Health ServiceNational Institutes of HealthU.S. Department of Health and Human Services
KeywordsReprogrammingInduced pluripotent stem cellSomatic cellInformed consentEngineering ethicsComputer scienceBiologyMedicineCellEmbryonic stem cellEngineeringGeneticsAlternative medicinePathology

Abstract

fetched live from OpenAlex

Human somatic cell reprogramming is a leading technology for accelerating disease modeling and drug discovery. Research organizations are sponsoring initiatives to create libraries of induced pluripotent stem cell (iPSC) lines for broad distribution and application. Donor informed consent plays a critical role in supporting the ethical conduct of iPSC research. To date, our organizations have focused on informed consent considerations for somatic cell collection intended specifically for iPSC derivation and distribution. This article considers how somatic cells obtained under general (biomedical) research protocols can be used for iPSC derivation. We present draft Points to Consider regarding the use of human somatic cells for iPSC research. Our goal is to initiate a process designed to develop consensus for the use of previously collected specimens for iPSC research. We anticipate publishing final considerations in early 2014.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.787

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.068
GPT teacher head0.338
Teacher spread0.270 · 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 designBench or experimental
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

Citations31
Published2013
Admission routes1
Has abstractyes

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