Interactions Between<i>syn</i>- and<i>anti</i>-2,3-Hexanediol Lures on Trap Catches of Woodboring Beetles and Associates in Southeastern United States
Bibliographic record
Abstract
In 2016, we conducted three experiments to clarify the effects of 2,3-hexanediols isomers on trap catches of Neoclytus acuminatus (F.) (Coleoptera: Cerambycidae). We also noted the effects of the isomers on trap catches of other cerambycids and associated species of predators and competitors. Catches of N. acuminatus in traps baited with ethanol + syn-2,3-hexanediol + racemic 3-hydroxyoctan-2-one were reduced with the addition of anti-2,3-hexanediol, an attractant for Curius dentatus Newman (Coleoptera: Cerambycidae). A fourth experiment conducted in 2017 verified that racemic 3-hydroxyoctan-2-one increases catches of N. acuminatus in traps baited with ethanol + syn-2,3-hexanediol. The addition of anti-2,3-hexanediol increased catches of Knulliana cincta (Drury) (Coleoptera: Cerambycidae) in traps baited with ethanol + racemic 3-hydroxyoctan-2-one, whereas attraction of Neoclytus scutellaris (Olivier) to traps baited with ethanol + racemic 3-hydroxyhexan-2-one was reduced by syn-2,3-hexanediol. Trap catches of the beetle predators Chariessa pilosa (Forster), Enoclerus ichneumonus (F.), and Madoniella dislocata (Say) (Coleoptera: Cleridae) were affected by 2,3-hexanediol isomers, whereas other common predators were unaffected by the isomers. Attraction of the bostrichid Xylobiops basilaris (Say) (Coleoptera: Bostrichidae) was increased by the 2,3-hexanediols; the relative effect of the two isomeric blends was dependent on trap co-baits of 3-hydroxy-2-ketones. The two enantiomeric blends of 2,3-hexanediol had minimal effects on catches of most species of ambrosia beetles, whereas the 3-hydroxy-2-ketones affected trap catches of some species.
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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".