Linking the Morphology of Sternal Glands to Rubbing Behavior by<i>Vespa soror</i>(Hymenoptera: Vespidae) Workers During Recruitment for Group Predation
Bibliographic record
Abstract
Abstract The activities of social insect colonies are supported by exocrine glands and the tremendous functional diversity of the compounds that they secrete. Many social wasps in the subfamilies Vespinae and Polistinae have two sternal glands—the van der Vecht and Richards’ glands—that vary in their features and function across the species in which they are found. Field observations suggest that giant hornets use secretions from the van der Vecht gland to chemically mark targeted nests when workers initiate group attacks on social insect prey. However, descriptions of giant hornets’ sternal glands and details about their recruitment behavior are lacking. We describe the morphology of the sternal glands of the giant hornet Vespa soror du Buysson and consider their potential to contribute to a marking pheromone. We also assess the gastral rubbing behavior of workers as they attacked Apis cerana F. (Hymenoptera: Apidae) colonies. V. soror workers have well-developed van der Vecht and Richards’ glands on their terminal gastral sternites, with morphologies that robustly support the synthesis, storage, and dissemination of their secretory products. Observations confirm that the van der Vecht gland is exposed during gastral rubbing, but that the Richards’ gland and glands associated with the sting apparatus may also contribute to a marking pheromone. Workers briefly but repeatedly rubbed their gasters around hive entrances and on overhead vegetation. Colonies were heavily marked over consecutive attacks. Our findings provide insight into the use of exocrine secretions by giant hornets as they recruit nestmates to prey colonies for group attacks.
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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 | 0.001 | 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".