MétaCan
Menu
Back to cohort
Record W2162014990 · doi:10.1002/bies.201200162

Would the real human embryonic stem cell please stand up?

2013· review· en· W2162014990 on OpenAlexaff
Ben Zhang, Roman Krawetz, Derrick E. Rancourt

Bibliographic record

VenueBioEssays · 2013
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsEpiblastReprogrammingEmbryonic stem cellCell biologyBiologyStem cellEmbryoGerm layerBlastocystGastrulationImmunologyInduced pluripotent stem cellGeneticsCellEmbryogenesisGene

Abstract

fetched live from OpenAlex

Embryonic stem cells (ESCs) are now classified into two types of pluripotency: "naïve" and "primed" based upon their differing characteristics. Conventional human ESCs have much more in common with mouse epiblast stem cells and are now deemed to be primed. Naïve human ESCs that resemble mouse ESCs have recently been generated from their primed counterpart by cellular reprogramming. Isolation of naïve hESCs from human embryos has proven to be difficult. Is the inability to capture naïve hESCs the result of suboptimal derivation conditions or because they are so transient they cannot be "captured" in vitro? Prevailing evidence surrounding this issue are inconclusive and require additional human embryo research. However, negative public opinion regarding human embryo research, may make this an uphill battle. The solution may come from cellular reprogramming.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.827
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.065
GPT teacher head0.343
Teacher spread0.278 · 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.

Study designNot applicable
Domainnot available
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

Citations10
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueBioEssaysSame topicPluripotent Stem Cells ResearchFrench-language works237,207