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Record W1578106937 · doi:10.1002/9780470514221.ch16

The Gene Trap Approach in Embryonic Stem Cells: The Potential for Genetic Screens in Mice

2007· review· en· W1578106937 on OpenAlexaff
Alexandra L. Joyner, Anna B. Auerbach, William C. Skarnes

Bibliographic record

VenueNovartis Foundation symposium · 2007
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Genetics and Reproduction
Canadian institutionsLunenfeld-Tanenbaum Research InstituteMount Sinai Hospital
Fundersnot available
KeywordsEmbryonic stem cellBiologyGeneGene knockinMutantExonGene targetingGeneticsPhenotypeStem cellMolecular biologylac operonCell biologyGene expression

Abstract

fetched live from OpenAlex

The gene trap approach in embryonic stem cells was developed as a means to screen for genes expressed during early postimplantation development in the mouse. We have validated the approach by showing that lacZ from the integrated vector is activated by splicing to endogenous exons and expressed in embryos in patterns that mimic those of the endogenous genes. These insertions can produce developmental defects in homozygous mice. The results indicate that a large screen of gene trap cell lines on the basis of embryonic lacZ expression is feasible and should provide a new source of genes, mouse mutants and mouse strains that express lacZ in particular domains and lineages. The gene trap approach could be extended to a smaller screen for genes based on mutant phenotypes.

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)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.007

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 head0.037
GPT teacher head0.303
Teacher spread0.266 · 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 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

Citations19
Published2007
Admission routes1
Has abstractyes

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