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Record W2901901698 · doi:10.1186/s13059-018-1577-z

Ten things you should know about transposable elements

2018· review· en· W2901901698 on OpenAlexafffund
Guillaume Bourque, Kathleen H. Burns, Mary Gehring, Vera Gorbunova, Andrei Seluanov, Molly Hammell, Michaël Imbeault, Zsuzsanna Izsvák, Henry L. Levin, Todd S. Macfarlan, Dixie L. Mager, Cédric Feschotte

Bibliographic record

VenueGenome biology · 2018
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicChromosomal and Genetic Variations
Canadian institutionsBC Cancer AgencyMcGill University
FundersNational Institute of General Medical SciencesNational Institute on AgingFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchEuropean CommissionWellcome TrustMcGill UniversityNational Cancer InstituteNational Institutes of HealthNational Science Foundation
KeywordsTransposable elementBiologyGenomeGenomicsEvolutionary biologyFunction (biology)Computational biologyGenome BiologyFunctional genomicsHuman geneticsGenome evolutionGeneticsGene

Abstract

fetched live from OpenAlex

Transposable elements (TEs) are major components of eukaryotic genomes. However, the extent of their impact on genome evolution, function, and disease remain a matter of intense interrogation. The rise of genomics and large-scale functional assays has shed new light on the multi-faceted activities of TEs and implies that they should no longer be marginalized. Here, we introduce the fundamental properties of TEs and their complex interactions with their cellular environment, which are crucial to understanding their impact and manifold consequences for organismal biology. While we draw examples primarily from mammalian systems, the core concepts outlined here are relevant to a broad range of organisms.

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)0.002
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 score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.003

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 head0.062
GPT teacher head0.297
Teacher spread0.235 · 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

Citations1,508
Published2018
Admission routes2
Has abstractyes

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