Development of an improved attractive lure for the pine shoot beetle, <i>Tomicus piniperda</i> (Coleoptera: Scolytidae)
Bibliographic record
Abstract
Abstract 1 The pine shoot beetle, Tomicus piniperda (L.) (Coleoptera: Scolytidae), is an exotic pest of pine, Pinus spp., and was first discovered in North America in 1992. 2 Although primary attraction to host volatiles has been clearly demonstrated for T. piniperda , the existence and role of secondary attraction to insect‐produced pheromones have been widely debated. 3 Currently, commercial lures for T. piniperda include only the host volatiles α‐pinene in North America and α‐pinene, terpinolene and (+)‐3‐carene in Europe. Several potential pheromone candidates have been identified for T. piniperda. 4 We tested various combinations of host volatiles and pheromone candidates in Michigan, U.S.A., and Ontario, Canada, to determine an optimal blend. 5 Attraction of T. piniperda was significantly increased when trans ‐verbenol (95% pure, 3.2% cis‐ verbenol content) was added with or without myrtenol to α‐pinene or to blends of α‐pinene and other kairomones and pheromone candidates. 6 Our results, together with other research demonstrating that trans ‐verbenol is produced by T. piniperda , support the designation of trans ‐verbenol as a pheromone for T. piniperda. A simple operational lure consisting of α‐pinene and trans ‐verbenol is recommended for optimal attraction of T. piniperda .
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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) | 0.002 | 0.001 |
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".