Modeling the Area-Wide Integration of Male Annihilation and the Simultaneous Release of Methyl Eugenol-Exposed<i>Bactrocera</i>spp. Sterile Males
Bibliographic record
Abstract
Abstract We present simple models that describe the factors influencing application of the Sterile Insect Technique (SIT) alone, followed by the factors affecting the integration of the Male Annihilation Technique (MAT) and SIT simultaneously to annihilate wild males and replace them with methyl eugenol (ME)-exposed sterile males that are less responsive to the toxic MAT baits. The removal by MAT of large numbers of males to deprive females of mates is rather ineffective to suppress populations unless a proportion of females are also attracted to baits. When simultaneously implementing SIT and MAT, much less stringent requirements for the annihilation of the wild male population apply and the sterile fly release rate can be reduced to only ≈5% of that when SIT is applied alone. The main determinants of control efficiency are whether a proportion of wild females is attracted to MAT baits, whether most of the wild males respond to the MAT baits before mating, and whether a majority of ME-exposed sterile males do not respond to the baits. However, a high remating frequency in mated females, and the release of only sterile males or both sterile males and females, do not greatly affect the ease of control. We conclude that the simultaneous MAT and SIT application is synergistic and the combination appears to be an extremely powerful control strategy for tephritid fruit fly pests that are attracted to ME.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".