Population genetic structure and genetic diversity of soybean aphid collections from the USA, South Korea, and Japan
Bibliographic record
Abstract
Following its recent invasion of North America, the soybean aphid (Aphis glycines Matsumura) has become the number one insect pest of soybean (Glycine max L. Merr.) in the north central states of the USA. A few studies have been conducted on the population genetic structure and genetic diversity of the soybean aphid and the source of its invasion in North America. Molecular markers, such as simple sequence repeats (SSRs) are very useful in the evaluation of population structure and genetic diversity. We used 18 SSR markers to assess the genetic diversity of soybean aphid collections from the USA, South Korea, and Japan. The aphids were collected from two sites in the USA (Indiana and South Dakota), two sites in South Korea (Yeonggwang district and Cheonan city), and one site in Japan (Utsunomiya). The SSR markers were highly effective in differentiating among aphid collections from different countries. The level of differentiation within each population and among populations from the same country was limited, even in the case of the USA where the two collection sites were more than 1200 km apart.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".