Data for: Sexual Selection and the Non-random Union of Gametes: Retesting for Assortative Mating by Fitness in Drosophila melanogaster
Bibliographic record
Abstract
While numerous theoretical population genetic models indicate that mating assortatively by genetic ‘quality’ in a species can enhance the efficiency of purging of deleterious mutations and/or the spread of beneficial alleles in the gene pool, empirical studies looking to quantify the extent of assortative mating by quality are surprisingly rare and largely inconclusive. Here, we set out to examine whether fruit flies (Drosophila melanogaster) engage in assortative mating by body-size phenotype, a composite trait strongly associated with both reproductive success and survival, and is considered a reliable indicator of natural genetic quality. Male and female flies of different body-size sizes classes (large and small) were obtained under the typical culture conditions to which they were adapted and placed into competitive reproductive conditions, so that their interactions and mating patterns could be measured. We found that flies engaged in assortative courting and mating behaviours and that they produced more offspring with similar sized individuals. Subsequent assays of offspring fitness indicated that assortative mating produced sons and daughters that had greater or equal reproductive success than those produced from disassortative mating. Together, these results validate theoretical predictions and demonstrate that assortative mating sexual selection can enhance the effects of natural selection and consequently the rate of adaptive evolution. The datasets archived here contain the observations on courtship rates, mating speeds, copulation durations, and offpring production that were obtained in our two sets of experiments. The data represents the results of experiments examining behaviour and reproductive success of fruit flies, Drosophila melanogaster. They are saved in .csv format.
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 | 0.004 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.090 | 0.041 |
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".