Scientific Opinion on the pest categorisation of Atropellis spp
Bibliographic record
Abstract
The European Commission requested the EFSA Panel on Plant Health to perform a pest categorisation of Atropellis spp., the fungal pathogens responsible for causing cankers in several Pinus species. The pathogens are listed in Annex IIAI of Directive 2000/29/EC. The pathogens have been identified as A. apiculata A. pinicola, A. piniphila and A. tingens. Detection, identification and differentiation of Atropellis species is based on their morphological and cultural characteristics. A. apiculata is present in North Carolina and Virginia (USA), and A. pinicola A. piniphila and A. tingens are present in Canada and the USA. Atropellis spp. are not known to occur in the EU Member States so far. Several Pinus species have been reported to be hosts of Atropellis spp., with some of them being present in the EU Member States. However, the susceptibility to infection with these pathogens of pine species native to Europe and Eurasia, such as Pinus brutia P. cembra P. mugo P. peuce P. pinaster and P. sibiricais not yet known. There are no obvious eco-climatic factors limiting the potential establishment and spread of the pathogens in the risk assessment area. The pathogens can spread over short distances by ascospores that are dispersed primarily by wind and secondarily by rain. Spread of Atropellis spp. over long distances may occur by means of movement of infected host plants for planting (especially asymptomatic), cut branches, and wood or isolated bark. Control methods used against Atropellis spp. include cultural practices and sanitary measures. No chemical control measures, resistant host genotypes or biological control measures exist. Potential consequences of the damage caused by Atropellis spp. include malformation of the trees resulting in lower wood quality or tree marketability.
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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 | 0.015 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".