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Record W4416328458 · doi:10.1016/j.cub.2025.10.044

Targeted cannibalism of queens mediated by worker signals in fire ants

2025· article· en· W4416328458 on OpenAlexaff
Liang Lü, Hualong Qiu, Jiamei Zhong, Siquan Ling, Jinzhu Xu, Laurent Keller

Bibliographic record

VenueCurrent Biology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInsect and Arachnid Ecology and Behavior
Canadian institutionsKellogg's (Canada)
FundersNational Natural Science Foundation of China
KeywordsCannibalismStridulationChemical communicationEusocialityFire antFormicoideaRange (aeronautics)Social grooming

Abstract

fetched live from OpenAlex

Ants employ a wide range of communication systems to coordinate colony functions, with chemical signals being the most extensively studied. While investigating social regulation in the invasive fire ant Solenopsis invicta, we discovered a striking behavior: under food-deprived conditions, workers frequently cannibalize a high proportion of virgin queens. Our experiments revealed that this behavior is triggered by nutritional stress and mediated by a specific vibrational signal (stridulation) produced by workers and directed at young queens. Chemical analyses showed no significant differences in cuticular hydrocarbons between targeted and non-targeted queens, providing no evidence that chemical cues are responsible for this behavior. In contrast, playback experiments demonstrated that queen cannibalism is directly induced by vibrational signals. These findings uncover a previously unrecognized role for stridulation in regulating social behavior and challenge the notion that non-chemical communication is secondary in ants.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.011
GPT teacher head0.297
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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