Bibliographic record
Abstract
Phenotypic plasticity is an important mechanism for populations to buffer themselves from environmental change. While it has long been appreciated that natural populations possess genetic variation in the extent of plasticity, a surge of recent evidence suggests that epigenetic variation could also play an important role in shaping phenotypic responses. Compared with genetic variation, epigenetic variation is more likely to have higher spontaneous rates of mutation and a more sensitive reaction to environmental inputs. In our review, we first provide an overview of recent studies on epigenetically encoded thermal plasticity in animals to illustrate environmentally-mediated epigenetic effects within and across generations. Second, we discuss the role of epigenetic effects during adaptation by exploring population epigenetics in natural animal populations. Finally, we evaluate the evolutionary potential of epigenetic variation depending on its autonomy from genetic variation and its transgenerational stability. Although many of the causal links between epigenetic variation and phenotypic plasticity remain elusive, new data has explored the role of epigenetic variation in facilitating evolution in natural populations. This recent progress in ecological epigenetics will be helpful for generating predictive models of the capacity of organisms to adapt to changing climates.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".