<i>Cryptostroma corticale</i> (Ellis & Everh.) P. H. Greg. & S. Waller causing sooty bark disease in British Columbia, Canada
Bibliographic record
Abstract
Sooty bark disease is an invasive disease causing significant mortality of sycamore maple (Acer pseudoplatanus L.) in Europe, where it is emerging due to increasing drought and heat events. The causal agent, Cryptostroma corticale (Ellis & Everh.) P. H. Greg. & S. Waller, is a fungus endemic to the Great Lake region in eastern Canada, where it does not appear to cause disease within its natural host range (e.g. sugar maple, Acer saccharum Marshall). Sooty bark disease was reported causing mortality on sycamore maple and additional species within Washington State beginning in 2017. In summer 2022, sooty bark disease was found on a sycamore maple near Vancouver, representing the first report of the disease and causal agent within the province of British Columbia (BC). In this study, we identify the causal agent of sooty bark disease by morphological and molecular methods and confirm its pathogenicity in a controlled growth chamber experiment fulfilling Koch’s postulates on sycamore maple. Cryptostroma corticale has so far been found in BC on sycamore maple, Norway maple (A. platanoides L.) and bigleaf maple (A. macrophyllum Pursh). Sooty bark disease has been previously shown to increase in severity and occurrence under drought and warm conditions; we anticipate rising sooty bark disease cases as BC experiences increasingly frequent and extreme summer droughts and heat events.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".