A Coordinated Sampling and Identification Methodology for Larval Parasitoids of Spotted-Wing Drosophila
Bibliographic record
Abstract
We provide recommendations for sampling and identification of introduced larval parasitoids of spotted-wing drosophila, Drosophila suzukii (Matsumura) (Diptera: Drosophilidae). These parasitoids are either under consideration for importation (aka classical) biological control introductions, or their adventive (presumed to have been accidentally introduced) populations have recently been discovered in North America and Europe. Within the context of the ecology of D. suzukii and its parasitoids, we discuss advantages and disadvantages of estimating larval parasitism levels using different methods, including naturally collected fruit samples and sentinel baits. For most situations, we recommend repeated sampling of naturally occurring fruit rather than using sentinel baits to monitor seasonal dynamics of host plant-Drosophila-parasitoid associations. We describe how to separate Drosophilidae puparia from host fruit material in order to accurately estimate parasitism levels and establish host-parasitoid associations. We provide instructions for identification of emerging parasitoids and include a key to the common families of parasitoids of D. suzukii. We anticipate that the guidelines for methodology and interpretation of results that we provide here will form the basis for a large, multi-research team sampling effort in the coming years to characterize the biological control and nontarget impacts of accidentally and intentionally introduced larval parasitoids of D. suzukii in several regions of the world.
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.012 |
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".