Differential response of male and female emerald ash borers (Col., Buprestidae) to (Z)‐3‐hexenol and manuka oil
Bibliographic record
Abstract
Abstract We conducted two trapping experiments in green ash plantations in Ontario, Canada to compare the response of the emerald ash borer (EAB), Agrilus planipennis , to (Z)‐3‐hexenol (Z3‐6:OH) and manuka oil. In the first experiment, Z3‐6:OH (7.6 mg/day) in purple prism traps hung 1.5 m above ground caught significantly more EAB than the unbaited controls, with male catches significantly greater than female catches at two locations. Manuka oil (50 mg/day) attracted equal numbers of males and females but they were significantly greater than the controls at only one location. Adding (Z)‐3‐hexenal or (Z)‐3‐hexenyl acetate in binary or ternary combinations with Z3‐6:OH did not enhance trap catch. In the second experiment, Z3‐6:OH released at two rates (7.6 or 80 mg/day) in light green prism traps placed in the ash canopy also caught significantly more males than females and more males than the unbaited controls or manuka oil‐baited traps. Manuka oil had no significant effect on catches relative to the controls. Combining Z3‐6:OH with manuka oil did not enhance catches of EAB. We conclude that there was a strong male‐biased EAB response to Z3‐6:OH lures, whereas manuka oil, when effective, attracted both sexes equally. Z3‐6:OH in light green prism traps in the canopy is an effective lure for EAB, particularly for males.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".