Data from: Comparing the intersex genetic correlation for fitness across novel environments in the fruit fly, Drosophila serrata
Bibliographic record
Abstract
Sexually antagonistic genetic variation can pose limits to the independent evolution and adaptation of the sexes. The extent of sexually antagonistic variation is reflected in the intersex genetic correlation for fitness (rwFM). Previous estimates of this correlation have been mostly limited to populations in environments to which they are already well adapted, making it difficult to gauge the importance of sexually antagonistic genetic variance during the early stages of adaptation, such as that occurring following abrupt environmental change or upon the colonization of new habitat. Here we assayed male and female lifetime fitness in a population of Drosophila serrata in four novel laboratory environments. We found that rwFM varied significantly across environments, with point estimates ranging from positive to negative values of considerable magnitude. We also found that the variability among estimates was because, at least in part, of significant differences among environments in the genetic variances of both male and female fitness, with no evidence of any significant changes in the intersex covariance itself, although standard errors of these estimates were large. Our results illustrate the unpredictable nature of rwFM in novel environments and suggest that, although sexually antagonistic genetic variance can be pronounced in some novel environments, it may have little effect in constraining the early stages of adaptation in others.
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 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.023 |
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".