Influence of trap colour, type, deployment height, and a host volatile on monitoring <i>Orchestes fagi</i> (Coleoptera: Curculionidae) in Nova Scotia, Canada
Bibliographic record
Abstract
Abstract Orchestes fagi (Linnaeus) (Coleoptera: Curculionidae) is a pest of beech trees (Fagus sylvatica Linnaeus; Fagaceae) in Europe that has recently become established and invasive on American beech (Fagus grandifolia Ehrhart) in Nova Scotia, Canada. We tested the effects of trap type, trap colour, trap height, and lure on the numbers of O. fagi captured per trap with the objective of developing a survey tool to monitor the weevil’s spread. We captured O. fagi in significantly greater numbers on yellow, green, or white traps than on light blue, dark blue, or red traps. There were no significant interactions between trap colour and trap design. Sticky triangular prism traps caught significantly more O. fagi than did nonsticky intercept traps regardless of colour. No effect of trap height was observed. Mean catch of O. fagi was significantly greater on yellow sticky triangular prism traps than on commercially sourced yellow sticky cards. Baiting yellow, green, or white sticky prism traps with the host volatile 9-geranyl-p-cymene did not increase catch of O. fagi. Our results suggest that yellow, green, or white sticky prism traps are a useful tool for detecting O. fagi adults and monitoring the spread of this species in Canada.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".