Data from: Assessing the potential of genotyping-by-sequencing-derived single nucleotide polymorphisms to identify the geographic origins of intercepted gypsy moth (Lymantria dispar) specimens: a proof-of-concept study
Bibliographic record
Abstract
AbstractForest invasive alien species are a major threat to ecosystem stability and can have enormous economic and social impacts. For this reason, preventing the introduction of Asian gypsy moths (AGM; Lymantria dispar asiatica and L. d. japonica) into North America has been identified as a top priority by North American authorities. The AGM is an important defoliator of a wide variety of hardwood and coniferous trees, displaying a much broader host range and an enhanced dispersal ability relative to the already established European gypsy moth (L. d. dispar). Although molecular assays have been developed to help distinguish gypsy moth subspecies, these tools are not adequate for tracing the geographic origins of AGM samples intercepted on foreign vessels. Yet, this type of information would be very useful in characterizing introduction pathways and would help North American regulatory authorities in preventing introductions. The present proof-of-concept study assessed the potential of single nucleotide polymorphism (SNP) markers, obtained through genotyping-by-sequencing (GBS), to identify the geographic origins of gypsy moth samples. The approach was applied to eight laboratory-reared gypsy moth populations, whose original stocks came from locations distributed over the entire range of L. dispar, comprising representatives of the three recognized subspecies. The various analyses we performed showed strong differentiation among populations (Fst ≥ 0.237), enabling clear distinction of subspecies and geographic variants, while revealing introgression near the geographic boundaries between subspecies. This strong population structure resulted in 100% assignment success of moths to their original population when 2327 SNPs were used. Although the SNP panels we developed are not immediately applicable to contemporary, natural populations because of distorted allele frequencies in the laboratory-reared populations we used, our results attest to the potential of genome-wide SNP markers as a tool to identify the geographic origins of intercepted gypsy moth samples.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".