Establishment of <i><scp>L</scp>olium</i> species resistant to acetolactate synthase‐inhibiting herbicide in and around grain‐importation ports in <scp>J</scp>apan
Bibliographic record
Abstract
Summary Compared with natural seed dispersal, human‐mediated seed dispersal could spread herbicide resistance genes on a much larger scale. Herbicide‐resistant weed seeds have been reported as contaminants in commercial grain. We investigated the contamination of seeds of Lolium species with target‐site mutations conferring resistance to acetolactate synthase (ALS)‐inhibiting herbicides in wheat imported from the USA, Canada and Australia into Japan. We also investigated the establishment of ALS‐inhibiting herbicide‐resistant Lolium species in 12 seaports in Japan that are major entry points for international commodities. We found herbicide‐resistant Lolium spp. seeds from all classes of wheat samples. Resistant individuals became established at six of eight ports where more than 50 kt of imported wheat is unloaded every year. The establishment of resistant Lolium spp. individuals was common at major grain landing ports. Monitoring over 3 years at one port revealed that the frequency of resistant individuals did not fluctuate between years. Many resistant individuals were distributed in front of the entrance of a fodder company, but a few resistant individuals were found in areas 2 km away from the port. The results indicate that gene flow is rare through pollen or seed movement from resistant plants to peripheral populations. Further extensive and long‐term monitoring is necessary to perform a comprehensive risk assessment of herbicide‐resistant plants entering Japan through major commercial ports.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".