Environmental influences on the epigenomes of herpetofauna and fish
Bibliographic record
Abstract
Herpetofauna (amphibians and reptiles) and fish represent important sentinel and indicator species for environmental and ecosystem health. It is widely accepted that the epigenome plays an important role in gene expression regulation. Environmental stimuli, including temperature and pollutants, influence gene activity, and there is growing evidence demonstrating that an important mechanism is through modulation of the epigenome. This has been primarily studied in human and mammalian models; relatively little is known about the impact of environmental conditions or pollutants on herpetofauna or fish epigenomes and the regulatory consequences of these changes on gene expression. Herein we review recent studies that have begun to address this deficiency, which have mainly focused on limited specific epigenetic marks and individual genes or large-scale global changes in DNA methylation, owing to the comparative ease of measurement. Greater understanding of the epigenetic influences of these environmental factors will depend on increased availability of relevant species-specific genomic sequence information to facilitate chromatin immunoprecipitation and DNA methylation experiments.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".