Evaluating methods to detect and monitor North American larval parasitoids of the emerald ash borer (Coleoptera: Buprestidae)
Bibliographic record
Abstract
Abstract Populations of native North American parasitoids attacking Agrilus Curtis (Coleoptera: Buprestidae) species have recently been considered as part of an augmentative biological control programme in an attempt to manage emerald ash borer, Agrilus planipennis Fairmaire, a destructive wood-boring beetle discovered in North America in 2002. We evaluate trapping methods to detect and monitor populations of two important native larval parasitoids, Phasgonophora sulcata Westwood (Hymenoptera: Chalcididae) and Atanycolus Förster (Hymenoptera: Braconidae) species, attacking emerald ash borer in its introduced range. We found that purple prism traps captured more P. sulcata than green prism traps, yellow pan traps, and log samples and thus were considered better for detecting and monitoring P. sulcata populations. Trap type did not affect the number of captures of Atanycolus species. Surprisingly, baiting prism traps with a green leaf volatile or manuka oil did not significantly increase captures of P. sulcata or Atanycolus species. Based on these results, unbaited purple prism traps would be optimal for sampling these native emerald ash borer parasitoids in long-term management programmes.
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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 | 0.001 | 0.001 |
| 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".