Semiochemicals for bark beetle (Coleoptera: Curculionidae) management in western North America: where do we go from here?
Bibliographic record
Abstract
Abstract This paper is intended as an assessment of the state of knowledge and development of semiochemical methods for control of bark beetles (Coleoptera: Curculionidae) in western North America and as a roadmap for future research and development in this field. It is based on a keynote presentation given at the symposium Managing Bark and Ambrosia Beetles with Semiochemicals , held in 2018 in Vancouver, British Columbia, Canada, at the Joint Meeting of the Entomological Society of America, the Entomological Society of Canada, and the Entomological Society of British Columbia. We describe currently available active ingredients, formulations, and release devices. Furthermore, we describe the most urgently needed new products and techniques, and constraints to their further development. Finally, we speculate about opportunities afforded by new advances in microbial synthesis of semiochemicals, streamlining of regulatory processing, and aerial application using unmanned aerial vehicles.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 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; both teacher heads agree on what is shown here.
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".