Potential for semiochemical-based monitoring of the pea leaf weevil (Coleoptera: Curculionidae) on field pea (Fabaceae) in the Canadian Prairie Provinces
Bibliographic record
Abstract
Abstract The pea leaf weevil, Sitona lineatus (Linnaeus) (Coleoptera: Curculionidae), is an important pest of field peas, Pisum sativum Linnaeus (Fabaceae), and faba beans, Vicia faba Linnaeus (Fabaceae), that has recently become established in the Prairie Provinces of Canada. Male pea leaf weevils produce an aggregation pheromone, 4-methyl-3,5-heptanedione, in the spring when overwintered weevils migrate to fields to feed and mate. The current study tests the attractiveness of the aggregation pheromone with and without synthetic bean volatiles to pea leaf weevils in the spring and in the fall when weevils seek perennial legumes to feed and overwinter. Modified Leggett traps similar to those used in Europe did not retain weevils in this study. Aggregation pheromone-baited pitfall traps caught male and female weevils in the spring and fall. Weevils were not attracted to traps baited with three bean volatiles, (Z)-3-hexen-1-yl acetate, (Z)-3-hexen-1-ol, and linalool. Bean volatiles did enhance response to pheromone, but only in the fall. Weevils were captured in most semiochemical-baited traps in a 1:1 sex ratio, but female-biased catch in control traps might indicate greater activity of females in the trap vicinity. This study lays the groundwork for semiochemical-based monitoring to detect pea leaf weevil spread in the Prairie Provinces.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".