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Record W3010528608 · doi:10.1111/eva.12946

Sources of epigenetic variation and their applications in natural populations

2020· article· en· W3010528608 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEvolutionary Applications · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsBiologyEpigeneticsVariation (astronomy)Phenotypic plasticityContext (archaeology)MicrobiomeEvolutionary biologyHolobiontPhenotypeEcologyComputational biologyGeneticsGeneSymbiosisBacteria

Abstract

fetched live from OpenAlex

Epigenetic processes manage gene expression and products in a real-time manner, allowing a single genome to display different phenotypes. In this paper, we discussed the relevance of assessing the different sources of epigenetic variation in natural populations. For a given genotype, the epigenetic variation could be environmentally induced or occur randomly. Strategies developed by organisms to face environmental fluctuations such as phenotypic plasticity and diversified bet-hedging rely, respectively, on these different sources. Random variation can also represent a proxy of developmental stability and can be used to assess how organisms deal with stressful environmental conditions. We then proposed the microbiome as an extension of the epigenotype of the host to assess the factors determining the establishment of the community of microorganisms. Finally, we discussed these perspectives in the applied context of conservation.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.782
Threshold uncertainty score0.432

Codex and Gemma teacher scores by category

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

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 head0.013
GPT teacher head0.247
Teacher spread0.234 · 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