Social structures depend on innate determinants and chemosensory processing in <i>Drosophila</i>
Bibliographic record
Abstract
Flies display transient social interactions in groups. However, whether fly-fly interactions are stochastic or structured remains unknown. We hypothesized that groups of flies exhibit patterns of social dynamics that would manifest as nonrandom social interaction networks. To test this, we applied a machine vision system to track the position and orientation of flies in an arena and designed a classifier to detect interactions between pairs of flies. We show that the vinegar fly, Drosophila melanogaster, forms nonrandom social interaction networks, distinct from virtual network controls (constructed from the intersections of individual locomotor trajectories). In addition, the formation of interaction networks depends on chemosensory cues. Gustatory mutants form networks that cannot be distinguished from their virtual network controls. Olfactory mutants form networks that are greatly disrupted compared with control flies. Different wild-type strains form social interaction networks with quantitatively different properties, suggesting that the genes that influence this network phenotype vary across and within wild-type populations. We have established a paradigm for studying social behaviors at a group level in Drosophila and expect that a genetic dissection of this phenomenon will identify conserved molecular mechanisms of social organization in other species.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".