Aerosol emitters disrupt codling moth, <i>Cydia pomonella</i>, competitively
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
BACKGROUND: Isomate(®) CM MIST aerosol emitters (Pacific BioControl Corp, Vancouver, WA) containing 36 g of codlemone, (E,E)-8,10-dodecadien-1-ol, were deployed at various densities in a commercial apple orchard to generate dosage-response profiles in order to elucidate the behavioral mechanism of disruption. RESULTS: Moth captures decreased asymptotically as Isomate(®) CM MIST densities increased. Data fitting to Miller-Gut and Miller-de Lame plots yielded straight lines, with positive and negative slopes respectively. Catch of male moths decreased from 28 trap(-1) in the control to 0.9 trap(-1) at the highest emitter density. Disruption of >90% was realized at emitter densities greater than 5 units ha(-1) . CONCLUSION: The resulting set of profiles explicitly matched the predictions for competitive rather than non-competitive disruption. Thus, these devices probably disrupt by inducing false-plume following rather than by camouflaging traps and females. The use of 5 MIST units ha(-1) would be necessary to achieve the same level of codling moth control provided by a standard pheromone treatment with passive reservoir dispensers. The need for only a few aerosol emitters, 2.5-5 units ha(-1) , mitigates the cost of labor required to hand-apply hundreds of passive reservoir dispensers; however, a potential weakness in using this technology is that the low deployment density may leave areas of little or no pheromone coverage, where mate finding may occur. This technology is likely to benefit substantially from treatment of large contiguous blocks of crop.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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