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Record W1711202046 · doi:10.1016/j.scr.2015.09.009

Reprogramming of mouse amniotic fluid cells using a PiggyBac transposon system

2015· article· en· W1711202046 on OpenAlexaff
Enrica Bertin, Martina Piccoli, Chiara Franzin, András Nagy, Maria Mileikovsky, Paolo De Coppi, Michela Pozzobon

Bibliographic record

VenueStem Cell Research · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsLunenfeld-Tanenbaum Research InstituteMount Sinai Hospital
FundersGreat Ormond Street Hospital CharityGreat Ormond Street Hospital for ChildrenNational Institute for Health and Care ResearchFondazione Cassa di Risparmio di Padova e Rovigo
KeywordsBiologyInduced pluripotent stem cellReprogrammingCell biologyKOSRSomatic cellGerm layerAmniotic fluidEmbryonic stem cellMolecular biologyTransposable elementStem cellCellGeneticsFetusGenomeGene

Abstract

fetched live from OpenAlex

Induced pluripotent stem (iPS) cells are generated from mouse and human somatic cells by forced expression of defined transcription factors using different methods. Amniotic fluid (AF) cells are easy to obtain from routinely scheduled procedures for prenatal diagnosis and iPS cells have been generated from human AF. Here, we generated iPS cells from mouse AF cells, using a non-viral-based approach constituted by the PiggyBac (PB) transposon system. All iPS cell lines obtained exhibited characteristics of pluripotent cells, including the ability to differentiate toward derivatives of all three germ layers in vitro and in vivo.

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)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.098
GPT teacher head0.344
Teacher spread0.247 · 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 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

Citations7
Published2015
Admission routes1
Has abstractyes

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