Evolution of sex: Using experimental genomics to select among competing theories
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Few topics have intrigued biologists as much as the evolution of sex. Understanding why sex persists despite its costs requires not just rigorous theoretical study, but also empirical data on related fundamental issues, including the nature of genetic variance for fitness, patterns of genetic interactions, and the dynamics of adaptation. The increasing feasibility of examining genomes in an experimental context is now shedding new light on these problems. Using this approach, McDonald et al. recently demonstrated that sex uncouples beneficial and deleterious mutations, allowing selection to proceed more effectively with sex than without. Here we discuss the insights provided by this study, along with other recent empirical work, in the context of the major theoretical models for the evolution of sex.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it