<scp>3‐Methylcyclohex</scp> ‐2‐en‐1‐one reduces the aggregation of <i>Dendroctonus pseudotsugae barragani</i> and corresponding mortality of <i>Pseudotsuga menziesii</i> in northern Mexico
Bibliographic record
Abstract
Abstract Dendroctonus pseudotsugae is the most important forest insect pest of Douglas‐fir Pseudotsuga menziesii in North America. Two subspecies of Douglas‐fir beetle are recognized: D . pseudotsugae pseudotsugae , which inhabits southwestern Canada and western United States, and Dendroctonus pseudotsugae barragani , which occurs in northern Mexico. This study aimed to determine the effectiveness of 3‐methylcylohex‐2‐en‐1‐one (MCH) in reducing aggregation of D . pseudotsugae barragani , and corresponding Douglas‐fir mortality by this insect. Two field experiments were conducted: the first consisted of three doses of MCH in bubble caps (plus a control treatment) applied within 16 0.5 ha plots. The second consisted of three doses of MCH disrupt micro‐flakes (plus a control treatment) applied within 16 1.0 ha plots. MCH bubble caps at 28.8 and 44.0 g AI/ha and MCH disrupt micro‐flakes at 185.3 and 741 g AI/ha significantly reduced the aggregation of D . pseudotsugae barragani . When applying MCH as bubble caps, only the highest dose (44.0 g AI/ha) significantly reduced the number of successfully attacked trees. However, MCH micro‐flake doses of 185.3 and 741 g AI/ha reduced the number of successfully attacked trees to zero.
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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) | 0.001 | 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".