Sex‐Specific Effects of Social Environment on Behaviour and Their Correlations in <scp><i>Drosophila melanogaster</i></scp>
Bibliographic record
Abstract
ABSTRACT Environmental and individual experiences can result in immediate and persistent changes in behaviour. Often, such effects are also sex‐dependent. Intraspecific interactions can be one of the most important environments an individual faces. Such social interactions are expected to affect a suite of behavioural traits and their correlations. Here, we used Drosophila melanogaster and high‐throughput automated behavioural phenotyping to determine how social environment (group mixed sex, group single sex, and social isolation) and sex interact to affect basic behaviours (exploration, movement within a y‐maze, and habituation to a startle) that likely underlie more complex behaviours such as mate searching and foraging. We show that such behaviours and some behavioural correlations are indeed context‐ and sex‐dependent. Males tended to show greater exploration, while females were more likely to show a habituation response to startle. Males and females from the mixed sex and isolated treatments showed opposite exploratory behaviour in the Y‐maze, and social treatment interacted with sex to affect the rate of habituation to a startle. Females also tended to have slightly stronger trait correlations compared to males. These results show that social environment and sex can play a significant role in shaping behaviour in Drosophila melanogaster. Our study provides insights into how the type of social stimulation and sex can interact to affect behaviours that are important in forming critical behaviours related to foraging and mate searching.
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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 | 0.000 |
| 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) | 0.001 | 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".