Assessment of Attractant Lures and Monitoring Traps for <i>Drosophila suzukii</i> (Diptera: Drosophidae) Using Electrophysiology, Laboratory Choice Assays, and Field Trials
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Monitoring is critical to control efforts for Drosophila suzukii Matsumura, an invasive polyphagous fly that has the potential to cause significant losses in commercial soft fruit and berry production worldwide. We used an iterative process to identify trap colors, trap designs, and volatile mixtures to improve monitoring efforts in commercial blueberry, raspberry, and blackberry crops. Our results suggest that the selection of trap color and design and attractant lures should be customized to the crop in which they are deployed. In raspberries grown in high tunnel systems, DrosaLure paired with Drosal traps painted green and purple were highly specific to D. suzukii although actual capture counts were low. However, in field grown raspberries, BioLure and Multilure traps were most effective, but with significant nontarget bycatch. In blueberries, we had greatest success with a 5 µg:50 ng mixture of ethyl acetate-acetoin in a green/purple-colored jar-style trap with large (5 cm) mesh covered openings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it