The gene “degrees of kevin bacon” (dokb) regulates a social network behaviour in Drosophila melanogaster
Bibliographic record
Abstract
Social networks are a mathematical representation of interactions among individuals which are prevalent across various animal species. Studies of human populations have shown the breadth of what can spread throughout a social network: obesity, smoking cessation, happiness, drug use and divorce. 'Betweenness centrality' is a key property of social networks that indicates an individual's importance in facilitating communication and cohesion within the network. Heritability of betweenness centrality has been suggested in several species, however the genetic regulation of this property remains enigmatic. Here, we demonstrate that the gene CG14109, referred to as degrees of kevin bacon (dokb), influences betweenness centrality in Drosophila melanogaster. We identify strain-specific alleles of dokb with distinct amino acid sequences and when the dokb allele is exchanged between strains, flies exhibit the betweenness centrality pattern dictated by the donor allele. By inserting a GAL4 reporter into the dokb locus, we confirm that dokb is expressed in the central nervous system. These findings define a novel genetic entry point to study social network structure and thereby establish gene-to-social structure relationships. While dokb sequence homology is exclusive to Diptera, we anticipate that dokb-associated molecular pathways could unveil convergent neural mechanisms of social behaviour that apply in diverse animal species.
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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) | 0.002 | 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".