Field type, trap type and field‐edge characteristics affect <i>Rhagoletis mendax</i> captures in lowbush blueberries
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: Blueberry maggot, Rhagoletis mendax Curran (Diptera: Tephritidae), is the most important pest of blueberries in eastern North America. Insecticide use in fruit-bearing lowbush blueberry fields could be reduced with management strategies focused on vegetative fields. Fly distribution and fruit infestation levels were assessed where fruit-bearing and vegetative fields adjoin and along forested edges of vegetative fields. RESULTS: Along adjoining edges, immature female flies were captured in fruiting fields and mature females in vegetative fields throughout the season. Male fly captures and fruit infestation levels were greater at 5 m than at 30 m from the edge. Along forested edges, fly captures were best predicted by densities of ripe lowbush blueberries and large coniferous trees. Maggot infestation level in lowbush blueberries was best predicted by blueberry density and small deciduous trees. Bunchberry, Cornus canadensis L., was the only non-crop host in which blueberry maggot was found. CONCLUSIONS: We have shown that relatively high numbers of flies occur in vegetative fields and at edges of fruiting fields. Ripe blueberries and certain vegetation in forested edges affect fly distribution and probably maintain populations. These results may help to predict where controls for blueberry maggot should be targeted and suggest that management strategies focused on vegetative fields and field edges may be worthwhile.
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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 | 0.000 | 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 | 0.000 | 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