Disruption of coniferophagous bark beetle (Coleoptera: Curculionidae: Scolytinae) mass attack using angiosperm nonhost volatiles: from concept to operational use
Bibliographic record
Abstract
Abstract Although the use of nonhost plants intercropped among host crops has been a standard agricultural practice for reducing insect herbivory for millennia, the use of nonhost signals to deter forest pests is much more recent, having been developed over the past several decades. Early exploratory studies with synthetic nonhost volatile semiochemicals led to targeted electrophysiological and trapping experiments on a variety of bark and ambrosia beetles (Coleoptera: Curculionidae: Scolytinae) across three continents. This work disclosed a suite of antennally and behaviourally active nonhost volatiles, which are detected in common across a range of coniferophagous bark beetles. It also established the fact that dispersing bark and ambrosia beetles detect nonhost signals while in flight and avoid nonhost trees without necessarily landing on them. Later work showed that groups of synthetic nonhost volatiles, sometimes combined with insect-derived antiaggregants, are effective in protecting individual trees and forest stands. Further work in this system may lead to the development of a variety of new and useful tactics for use in various integrated pest management strategies.
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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".