Data from: Genomic signatures of adaptation in native lizards exposed to human-introduced fire ants
Bibliographic record
Abstract
Understanding the process of genetic adaptation in response to human-mediated ecological change will help elucidate the eco-evolutionary impacts of human activity. In the 1930s red imported fire ants (Solenopsis invicta) were accidently introduced to the Southeastern USA, where today they are both venomous predators and toxic prey to native eastern fence lizards (Sceloporus undulatus). Here, we investigate potential lizard adaptation to invasive fire ants by generating whole-genome sequences from 420 lizards across three populations: one with long exposure to fire ants, and two unexposed populations. Signatures of positive selection exclusive to the exposed population overlap immune system, growth factor pathways, and morphological development genes. Among invaded lizards, longer limbs (used to remove stinging ants) are associated with increased survival. We identify alleles associated with longer limbs that are highly differentiated from the unexposed populations, a pattern counter to the pre-invasion latitudinal cline for limb lengths based on museum specimens. While we cannot rule out other environmental differences between populations driving these patterns, these results do constitute plausible genetic adaptations in lizards invaded by fire ants.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.007 |
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".