Using Flies to Understand Social Networks
Bibliographic record
Abstract
Many animals live in groups and interact with each other, creating an organized collective structure. Social network analysis (SNA) is a statistical tool that aids in revealing and understanding the organized patterns of shared social connections between individuals in groups. Surprisingly, the application of SNA revealed that Drosophila melanogaster , previously considered a solitary organism, displays group dynamics and that the structure of group life is inherited. Although the number of studies investigating Drosophila social networks is currently limited, they address a wide array of questions that have only begun to capture the details of group level behavior in this insect. Here, we aim to review these studies, comparing their respective scopes and the methods used, to draw parallels between them and the broader body of knowledge available. For example, we highlight how despite methodological differences, there are similarities across studies investigating the effects of social isolation on social network dynamics. Finally, this review aims to generate hypotheses and predictions that inspire future research in the emerging field of Drosophila social networks.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".