Small‐plot studies comparing pheromone and juice baits for mass‐trapping invasive <i><scp>S</scp>ynanthedon myopaeformis</i> in <scp>C</scp>anada
Bibliographic record
Abstract
Abstract Recent introduction of S ynanthedon myopaeformis ( B orkhausen) ( L epidoptera: S esiidae) into organic apple‐growing areas of C anada has stimulated research on semiochemical‐based management of this E uropean pest. Replicated, small‐plot (0.16 ha) experiments were conducted to compare sex pheromone, 3 Z ,13 Z ‐octadecadienyl acetate (10 mg), C oncord grape juice (300 ml), or their combination, as mass‐trapping lures at trap densities equivalent to 12.5, 25, 50, and 100 traps ha −1 . Total numbers of male and female moths removed from test plots increased significantly with trap density in all juice‐based mass‐trapping experiments. In pheromone mass‐trapping experiments, however, total catches of males did not increase significantly as trap densities were increased and catches appeared to plateau with 25–50 traps ha −1 . With pheromone‐based mass‐trapping, significantly fewer males were caught in pheromone‐baited assessment traps at the centre of each mass‐trapping plot than in identical traps in untreated plots. This reduction is indicative of significant trap interference or trap ‘shut‐down’. Increasing the density of juice‐based mass‐trapping had no effect on catches of male or female moths in juice‐baited assessment traps, indicating a short range of attraction and lack of interference between juice traps. Pheromone‐ and juice‐based mass trapping removed similar numbers of males at each trap density tested, respectively, but summed catches of males and females were greatest with juice baits. Combining pheromone and juice into a single mass‐trapping treatment (50 traps ha −1 ) did not significantly increase catches of males or females relative to either treatment alone. If a practical bisexual mass‐trapping system is going to be developed for S . myopaeformis , then identification of volatile kairomones in C oncord grape juice may be useful.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".