Known Distribution of the Soybean Cyst Nematode, <i>Heterodera glycines</i>, in the United States and Canada, 1954 to 2017
Bibliographic record
Abstract
The soybean cyst nematode (SCN) is a major yield-reducing pathogen of soybeans in North America. The nematode is an introduced pest and, therefore, knowledge of the distribution of SCN can be helpful in identifying areas where scouting and management efforts should be focused. Such information is especially important because yield-reducing infestations of SCN can occur without obvious above-ground symptoms appearing. In late 2016, nematologists, plant pathologists, and state plant regulatory officials from the soybean-producing states in the United States and provinces in Canada were queried to obtain the latest information on where the nematode had been found. An updated map of the known distribution of SCN in North America was also created. There were 17 states in which SCN was newly found since 2014, when the map was last updated, including the first discovery of SCN in the state of New York. North Dakota was the state with the greatest number of counties, seven, in which SCN had been newly discovered since 2014. This updated information illustrates that the nematode continues to spread throughout the soybean-growing areas of the continent and emphasizes that continued efforts to scout for and manage SCN are warranted.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".