THE ECOLOGY AND GENETICS OF FITNESS IN CHLAMYDOMONAS. XII. REPEATED SEXUAL EPISODES INCREASE RATES OF ADAPTATION TO NOVEL ENVIRONMENTS
Bibliographic record
Abstract
We investigated the dynamics of adaptation of the unicellular chlorophyte Chlamydomonas reinhardtii to new and hostile conditions of growth provided by novel carbon substrates in the dark. The experiment was designed to contrast perennially asexual lines with lines that had experienced one or more sexual episodes. All lines were capable of adapting to the novel environment. The sexual lines, however, showed greater adaptation over the course of the experiment, especially in more complex environments. Moreover, the effect of sex on adaptation increased with the number of successive sexual episodes. The time-course of adaptation showed that sex initially caused an increase in the standardized variance of fitness and an initial drop in mean fitness, at least after a second or third sexual episode. These short-term effects were followed by a period of recovery during which the fitness of sexual lines eventually exceeded that of asexual lines. The increase in mean fitness was mirrored by a decrease in the standardized variance of fitness relative to asexuals, suggesting that directional selection used up the variation generated by meiotic recombination and thereby conferred a fitness advantage to the sexual lines. These results support the Weismann-Fisher-Muller hypothesis for the maintenance of sex in natural populations.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 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".