Genetic variation of male reproductive success in a laboratory population of Anopheles gambiae
Bibliographic record
Abstract
BACKGROUND: For Anopheline mosquitoes, the vectors of human malaria, genetic variation in male reproductive success can have important consequences for any control strategy based on the release of transgenic or sterile males. METHODS: A quantitative genetics approach was used to test whether there was a genetic component to variation in male reproductive success in a laboratory population of Anopheles gambiae. Swarms of full sibling brothers were mated with a fixed number of females and their reproductive success was measured as (1) proportion of ovipositing females, (2) proportion of ovipositing females that produced larvae, (3) proportion of females that produced larvae, (4) number of eggs laid per female, (5) number of larvae per ovipositing female and (6) number of larvae per female. RESULTS: The proportion of ovipositing females (trait 1) and the proportion of ovipositing females that produced larvae (trait 2) differed among full sib families, suggesting a genetic basis of mating success. In contrast, the other measures of male reproductive success showed little variation due to the full sib families, as their variation are probably mostly due to differences among females. While age at emergence and wing length of the males were also heritable, they were not associated with reproductive success. Larger females produced more eggs, but males did not prefer such partners. CONCLUSION: The first study to quantify genetic variation for male reproductive success in A. gambiae found that while the initial stages of male reproduction (i.e. the proportion of ovipositing females and the proportion of ovipositing females that produced larvae) had a genetic basis, the overall reproductive success (i.e. the mean number of larvae per female) did not.
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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 | 0.001 | 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) | 0.001 | 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".