Data from: Evolution of sociability by artificial selection
Bibliographic record
Abstract
There has been extensive research on the ecology and evolution of social life in animals that live in groups. Less attention, however, has been devoted to apparently solitary species even though recent research indicates that they also possess complex social behaviors. To address this knowledge gap, we artificially selected on sociability, defined as the tendency to engage in non-aggressive activities with others, in fruit flies. Our goal was to quantify the factors that determine the level of sociability and the traits correlated with this feature. After 25 generations of selection, the high sociability lineages showed sociability scores about 50% higher than did the low sociability lineages. Experiments using the evolved lineages indicated that there were no differences in mating success between flies from the low and high lineages. Both males and females from the low lineages, however, were more aggressive than males and females from the high lineages. Finally, the evolved lineages maintained their sociability scores after ten generations of relaxed selection, suggesting no costs to maintaining low and high sociability, at least under our settings. Sociability is a complex trait, which we currently assess through genomic work on the evolved lineages.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.033 |
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".