Farm-level Losses and Grower Willingness to Try Management Strategies for Swede Midge in Vegetable Crops
Bibliographic record
Abstract
Since its introduction to North America in the 1990s, the invasive swede midge ( Contarinia nasturtii ) has become an important pest of cruciferous (Brassicaceae) vegetables in the northeast and Great Lakes regions of the United States and the Canadian provinces of Québec and Ontario. Swede midge reduces yield in cruciferous vegetables through larval feeding that distorts growth. Overlapping generations, cryptic larval feeding, and lack of effective biopesticides pose challenges for managing swede midge effectively using current tools. In 2018, we distributed an online survey for commercial vegetable growers in the United States and Canada to measure farm-level economic impacts of swede midge and grower perspectives on new management strategies for this pest. Growers reported losing $3808 US ($4890 Canadian) on average per acre per year due to swede midge–related vegetable crop losses. Both organic and conventional growers expressed an interest in paying more for nonchemical swede midge management vs. insecticides and were interested in trying new management strategies, particularly biological control.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".