Data from: Sexual conflict and social networks in bed bugs: Effects of social experience
Bibliographic record
Abstract
Living in groups can provide essential experience that improves sexual performance and reproductive success. While the effects of social experience have drawn considerable scientific interest, commonly used behavioural assays often do not capture the dynamic nature of interactions within a social group. Here, we conducted three experiments using a social network framework to test whether social experience during early adulthood improves the sexual competence of bed bugs (Cimex lectularius) when placed in a complex and competitive group environment. In each experiment, we observed replicate groups of bed bugs comprising previously socialized and previously isolated individuals of the same sex, along with an equal number of standardized individuals of the opposite sex. Regardless of whether we controlled for their insemination history, previously isolated males mounted and inseminated females at significantly higher rates than previously socialized males. However, we found no evidence of social experience influencing our other measures of sexual competence: proportion of mounts directed at females, ability to overcome female resistance, and strength of opposite-sex social associations. We similarly did not detect effects of social experience on our female sexual competence metrics: propensity to avoid mounts, rate of successfully avoiding mounts, opposite-sex social association strength, and rate of receiving inseminations. Our findings indicate that early social experience does not improve sexual competence in male and female bed bugs.
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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.023 |
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".