Experimentally guided development of a food bait for European fire ants
Bibliographic record
Abstract
Abstract Deployment of lethal food baits could become a control tactic for the invasive European fire ant (EFA), Myrmica rubra L. (Hymenoptera: Formicidae), because foraging ants carry the lethal food to their nest and share it with their nest mates, ultimately causing the demise of nests. Our objective was to develop a food bait that elicits a strong foraging response from EFAs, has extended shelf life, and is cost‐effective to produce. To develop a bait composition with ‘ant appeal’, we ran two separate field experiments testing pre‐selected carbohydrate sources (oranges, apples, bananas) and protein/lipid sources [tuna, pollen, sunflower seeds, mealworms (Tenebrio molitor L., Coleoptera: Tenebrionidae)]. Whereas foraging EFAs responded equally well to the three types of carbohydrates, they preferred mealworms to all other protein/lipid sources. In a follow‐up laboratory experiment, the combination of apples and mealworms elicited a stronger foraging response from EFAs than either apples or mealworms alone. To help reduce bait ingredient costs, we tested house crickets, Acheta domesticus (L.) (Orthoptera: Gryllidae), as a less expensive mealworm alternative and found crickets and mealworms comparably appealing. Addressing the shelf life of baits, we tested freeze‐dried and heat‐dried apple/cricket combinations. Rehydrated freeze‐dried baits proved as appealing as fresh baits and superior to rehydrated heat‐dried baits, suggesting that freeze‐drying may retain essential nutrients and/or aroma constituents. Insecticide‐laced baits had no off‐putting effect on foraging responses of worker ants and caused significant mortality. As freeze‐drying is expensive, further research should investigate the preservation of moist food baits or the development of dry baits that are hydrated prior to deployment.
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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) | 0.000 | 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 | 0.001 | 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".