Fungi Associated with Damage Observed on Branches of <i>Juglans nigra</i> in Indiana, Missouri, and Tennessee
Bibliographic record
Abstract
Branch and stem cankers caused by Geosmithia morbida associated with mass attack by its primary insect vector (Pityophthorus juglandis) result in thousand cankers disease (TCD) on Juglans and Pterocarya species. Because other fungi and insects can cause visible damage to Juglans nigra, a baseline assessment was performed to document damage types present and to characterize fungi associated with each type. Two branches were collected from trees with visually healthy crowns in TCD-free locations (Indiana and Missouri) and two branches from trees with and without crown symptoms characteristic of TCD within the disease range in Tennessee. In most cases, one of the two branches was girdled at the base 3 to 4 months prior to harvest. Outer bark was peeled from branch subsamples, observed damage characterized, and isolation of fungi from each damage type attempted. Three known pathogens of J. nigra were obtained from different damage types: G. morbida, in Tennessee only; Botryosphaeria dothidea, in Indiana and Tennessee; and Fusarium solani (= members of F. solani species complex), in all three states. The latter two fungi may exacerbate branch dieback and mortality of TCD-affected trees. These results will be of value to plant health specialists monitoring J. nigra in the field and laboratory diagnosticians processing survey 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".