Response of the whitespotted sawyer beetle, <i>Monochamus s. scutellatus</i>, and associated woodborers to pheromones of some <i>Ips</i> and <i>Dendroctonus</i> bark beetles
Bibliographic record
Abstract
Abstract: The response of whitespotted sawyer beetle, Monochamus s. scutellatus , to pheromones of the bark beetles, Dendroctonus rufipennis, Ips pini , Ips perturbatus and Ips latidens , and α ‐pinene was investigated with field‐trapping experiments. Traps baited with ipsenol caught significantly more M. s. scutellatus than unbaited traps, whereas the other compounds (ipsdienol, ipsdienol plus lanierone, ipsdienol plus cis ‐verbenol or frontalin) did not. Combining α ‐pinene with ipsdienol, ipsdienol plus lanierone, ipsdienol plus cis ‐verbenol or with frontalin did not increase captures of M. s. scutellatus above those of α ‐pinene alone, whereas the combination of α ‐pinene with ipsenol did. When α ‐pinene was combined with ipsdienol or frontalin, trap captures of Monochamus mutator were significantly higher than unbaited traps or traps baited with frontalin but were not higher than traps baited with α ‐pinene. The combination of ipsenol and α ‐pinene was significantly more attractive to Monochamus notatus than unbaited traps; however, traps containing either ipsenol or α ‐pinene were as attractive as the combination. None of the species of Buprestidae ( Buprestis maculativentris and Chalcophora virginiensis ) responded significantly to any of the treatments.
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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 | 0.000 |
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".