Semiochemistry and chemical ecology of the emerald ash borer<i>Agrilus planipennis</i>(Coleoptera: Buprestidae)
Bibliographic record
Abstract
Abstract The emerald ash borer (EAB),Agrilus planipennisFairmaire (Coleoptera: Buprestidae) is a very serious invasive pest in North America, causing extremely high levels of mortality to ash trees (FraxinusLinnaeus, Oleaceae) in the United States of America and Canada. Knowledge of buprestid chemical ecology is sparse, but the appearance of EAB in North America and its devastating ecological and economic impacts, particularly in the urban environment, have provided an opportunity to study the semiochemistry, natural history, and ecology of this buprestid in detail. This review will summarise the chemical ecology of EAB to date, discussing studies on semiochemistry, natural history, and behaviour with respect to host and mate finding that have identified several female-produced pheromone components (contact and sex pheromones), and attractive host kairomones. Earlier reviews focused on studies of attractive host volatiles with respect to development of a trapping system and visual and contact phenomena in EAB mate finding. This has led to the development of an efficient trapping system for EAB, with attempts to optimise the range of variables in trap protocols, combining pheromone components, release rates, and combinations with host kairomones, as well as trap type, placement, height, and colour being taken into account.
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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".