Epigenetic pathways through which experiences become linked with biology
Bibliographic record
Abstract
This article highlights the defining principles, progress, and future directions in epigenetics research in relation to this Special Issue. Exciting studies in the fields of neuroscience, psychology, and psychiatry have provided new insights into the epigenetic factors (e.g., DNA methylation) that are responsive to environmental input and serve as biological pathways in behavioral development. Here we highlight the experimental evidence, mainly from animal models, that factors such as psychosocial stress and environmental adversity can become encoded within epigenetic factors with functional consequences for brain plasticity and behavior. We also highlight evidence that epigenetic marking of genes in one generation can have consequences for future generations (i.e., inherited), and work with humans linking epigenetics, cognitive dysfunction, and psychiatric disorder. Though epigenetics has offered more of a beginning than an answer to the centuries-old nature-nurture debate, continued research is certain to yield substantial information regarding biological determinants of central nervous system changes and behavior with relevance for the study of developmental psychopathology.
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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 | 0.000 | 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 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".