Trap catches of woodboring beetles and predators affected by release rates of cerambycid pheromones
Bibliographic record
Abstract
Detection programs for nonnative species of woodboring beetles require effective and affordable traps and lures. 3-Hydroxyhexan-2-one, 3-hydroxyoctan-2-one, and syn-2,3-hexanediol are 3 semiochemicals that are broadly attractive to longhorn beetles, and associated species of ambrosia beetles and predators. We determined the dose responses of insects to traps baited with ethanol and various combinations of these pheromones released at high rates versus low or medium rates. Five species of longhorn beetles exhibited positive dose-dependent responses with trap catches increasing with increased release rates. In contrast, 2 species of longhorn beetles exhibited a negative dose-dependent response to these pheromones. Curius dentatus Newman and Euderces pini Olivier (Coleoptera: Cerambycidae) were unaffected by release rates. Similar response patterns were observed with some species of ambrosia beetles (Coleoptera: Curculionidae), a powderpost beetle (Coleoptera: Bostrichidae), 3 predator species (Coleoptera: Carabidae, Cleridae, Trogossitidae), and an assassin bug (Hemiptera: Reduviidae). The reasons for these responses are unclear. However, the variation in dose-dependent responses by beetles may be important in optimizing the efficiency of detection programs with respect to lure costs and numbers of traps that should be deployed.
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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 | 0.001 |
| 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".