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Record W2011832001 · doi:10.1371/journal.pgen.0020002

Retroviral Elements and Their Hosts: Insertional Mutagenesis in the Mouse Germ Line

2006· article· en· W2011832001 on OpenAlexafffund
Irina A. Maksakova, Mark T. Romanish, Liane Gagnier, Catherine A. Dunn, Louie N. van de Lagemaat, Dixie L. Mager

Bibliographic record

VenuePLoS Genetics · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicChromosomal and Genetic Variations
Canadian institutionsUniversity of British ColumbiaBC Cancer Agency
FundersBC Cancer AgencyCanadian Institutes of Health Research
KeywordsBiologyEndogenous retrovirusInsertional mutagenesisTransposable elementGeneticsMutagenesisGermlineGeneGenomeMutationRetrotransposonLaboratory mouse

Abstract

fetched live from OpenAlex

The inbred mouse is an invaluable model for human biology and disease. Nevertheless, when considering genetic mechanisms of variation and disease, it is important to appreciate the significant differences in the spectra of spontaneous mutations that distinguish these species. While insertions of transposable elements are responsible for only approximately 0.1% of de novo mutations in humans, the figure is 100-fold higher in the laboratory mouse. This striking difference is largely due to the ongoing activity of mouse endogenous retroviral elements. Here we briefly review mouse endogenous retroviruses (ERVs) and their influence on gene expression, analyze mechanisms of interaction between ERVs and the host cell, and summarize the variety of mutations caused by ERV insertions. The prevalence of mouse ERV activity indicates that the genome of the laboratory mouse is presently behind in the "arms race" against invasion.

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 score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.019
GPT teacher head0.201
Teacher spread0.181 · 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

Citations363
Published2006
Admission routes2
Has abstractyes

Explore more

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