Development of Primers Specific for Detection of <i>Litylenchus crenatae</i>, the Causal Agent of Beech Leaf Disease, in Plant Tissue
Bibliographic record
Abstract
Beech leaf disease (BLD), an emerging threat to American beech (Fagus grandifolia) in the northern United States and Canada, was recently confirmed to be caused by the nematode Litylenchus crenatae subsp. mccannii (hereafter L. crenatae). Consequently, there is a need for a rapid, sensitive, and accurate method for detecting L. crenatae for both diagnostic as well as control purposes. This research developed a new set of DNA primers that specifically amplify L. crenatae and allow for accurate detection of the nematode in plant tissue. These primers have also been used in quantitative PCR (qPCR) to determine relative differences in gene copy number between samples. This primer set provides an improved, effective tool for monitoring and detecting L. crenatae in temperate tree leaf tissue which is necessary to understand the spread of this emerging forest pest and to develop management strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".