Re-investigating monitoring tools for <i>Sitodiplosis mosellana</i> (Diptera: Cecidomyiidae) on the Canadian Prairies
Bibliographic record
Abstract
Abstract Sitodiplosis mosellana (Géhin) (Diptera: Cecidomyiidae) is a significant pest of wheat, Triticum aestivum Linnaeus (Poaceae), in Canada. Monitoring currently relies on labour-intensive counts of ovipositing females. Although traps baited with S. mosellana pheromone are used as decision support tools in the United Kingdom, in Canada, they are considered reliable only to indicate adult activity. Recent findings show that variability in pheromone release from commercial lures affects the number of midges captured and limits the reliability of pheromone monitoring. Here, two lure types and two trap types were compared for their ability to attract and retain S. mosellana males. We then compared the number of males captured in pheromone traps with the information provided by other monitoring tools, including emergence traps, soil cores, and ovipositing female counts. Jackson traps with Trécé rubber septa lures captured the most midges. The number of males captured in pheromone-baited traps was not related to overwintering, ovipositing, or emerging populations, suggesting that pheromone traps may not accurately reflect S. mosellana populations under field conditions. Variability in extracted pheromone amount between lures, regional climate, and Canada’s vast wheat-growing area may limit the development of an effective pheromone-based decision support tool for this region. Nevertheless, refinement of lure formulation, standardisation of trapping protocols, and integration of complementary monitoring approaches may enhance trap reliability and support a stronger monitoring system.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".