The Influence of Pruning on Wasp Inhabitants of Galls Induced by Hemadas nubilipennis Ashmead (Hymenoptera: Pteromalidae) on Lowbush Blueberry
Bibliographic record
Abstract
The efficacy of pruning methods for managing blueberry stem galls caused by the chalcid wasp, Hemadas nubilipennis (Ashmead), was studied in five commercial lowbush blueberry (Vaccinium angustifolium Aiton) fields in Nova Scotia, Canada, between October 1999 and May 2000. Blueberry fields were mowed in the fall, and burning treatments were subsequently applied either in the fall or the spring. Three treatments were compared: mowing only, mowing plus fall burning, and mowing plus spring burning. Galls collected from the mow plus spring-burn treatment had the least wasp emergence of the three treatments, while the total number of galls was not affected by treatment. Wasp mortality, not gall destruction, is why wasp emergence is reduced in burn treatments. More galls were located and, for the burn treatments, higher wasp emergence was seen from galls found within the leaf litter than those above it. Five co-inhabitants emerged from blueberry stem galls in this study. Three, Eurytoma solenozopheriae (Ashmead), Sycophila vacciniicola (Balduf), and Orymus vacciniicola (Ashmead) are commonly found associates. The other two, Eupelmus vesicularis (Ritzius) and Pteromalus spp., are new records for Nova Scotia. O. vacciniicola is likely an inquiline because it is the largest wasp emerging from galls, and there was a positive relationship between its emergence and that of H. nubilipennis. Larger gall size improved H. nubilipennis emergence from mow and spring-burn galls. After a field has been mowed in the fall, we recommend a spring burn to reduce gall populations and the threat of product contamination.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.000 | 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 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".