Optimization of Pheromone Traps for Coryphodema tristis (Lepidoptera: Cossidae)
Bibliographic record
Abstract
The Coryphodema tristis (Drury) is an important pest of Eucalyptus nitens (Deane and Maiden) plantations in South Africa. The gregarious larvae of this pest cause damage by feeding on the tree sapwood, and adults emerge in spring each year. The aim of this study was to optimize pheromone traps for operational use in management programs. This was achieved by investigating different pheromone blend combinations and trap types for efficacy under field conditions. Our results confirm that the cross vane bucket funnel trap baited with a 95:2.5:2.5 volumetric blend of Z9-14:OAc, Z9-14:OH, and 14Ac was superior to similarly baited standard bucket funnel and delta traps. We also estimated the release rate and ratios of the pheromone compounds loaded into an artificial permeation dispenser through solid-phase microextraction sampling. Results showed that the released blend of pheromone compounds mirrored the dispensed ratios relatively accurately and that release rates are affected by temperature.
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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) | 0.001 | 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".