A TaqMan Assay for the Detection and Monitoring of Potentially Invasive Lasiocampids, With Particular Attention to the Siberian Silk Moth, <i>Dendrolimus sibiricus</i> (Lepidoptera: Lasiocampidae)
Bibliographic record
Abstract
The Siberian silk moth, Dendrolimus sibiricus Tschetverikov, is a very serious pest of conifers in Russia and is an emerging threat in North America where an accidental introduction could have devastating impacts on native forest resources. Other Dendrolimus Germar species and related Eurasian lasiocampids in the genus Malacosoma (Hubner) could also present a risk to North America's forests. Foreign vessels entering Canadian and U.S. ports are regularly inspected for Lymantria dispar (Linnaeus) and for the presence of other potentially invasive insects, including suspicious lasiocampid eggs. However, eggs are difficult to identify based on morphological features alone. Here, we report on the development of two TaqMan (Roche Molecular Systems, Inc., Rotkreuz, Switzerland) assays designed to assist regulatory agencies in their identification of these insects. Developed using the barcode region of the cytochrome c oxidase I (COI) gene and run in triplex format, the first assay can detect Dendrolimus and Malacosoma DNA, and can distinguish North American from Eurasian Malacosoma species. The second assay is based on markers identified within the internal transcribed spacer 2 (ITS2) region and was designed to specifically identify D. sibiricus, while discriminating closely related Dendrolimus taxa. In addition to providing direct species identification in the context of its use in North America, the D. sibiricus assay should prove useful for monitoring the spread of this pest in Eurasia, where its range overlaps with those of the morphologically identical D. superans (Butler) and similar D. pini (Linnaeus). The assays described here can be performed either in the lab on a benchtop instrument, or on-site using a portable machine.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".