Bibliographic record
Abstract
We are pleased to include in this issue a number of papers arising from a successful workshop held in Parma, Italy, in April 2014, under the title ‘Data collection and information sharing in plant health’. The subject reflects the importance of those activities in improving the way we identify and manage risks. That the workshop was organised jointly by the European Food Safety Authority and EPPO is testament to the close working relationship which has developed between the two organisations but which continues to respect their different remits and geographical coverage. Another form of collaboration reported in this issue is the Euphresco network for plant health research programme funders and managers. Last year Euphresco became a self-sustaining network hosted by EPPO. The first call for research topics since that change of status was launched in November 2014, and following a consolidation and selection process 25 high-priority research topics have been identified by Euphresco members for funding. Information on the funded research projects will be available from the Euphresco website during the autumn 2015. New members from Serbia and Canada have recently indicated their intention to join the network, and enquiries from other countries and organisations are welcome. On the subject of sharing information, a number of papers in this issue present news about changing geographical or host ranges of pests. New pathways may also lead to new risks, sometimes in ways which are not predicted or predictable by plant health services. The DROPSA study reported here represents an effort to improve preparedness by obtaining and sharing information on pests which may be spread into and within the region on fruit, drawing on interception and outbreak data. Woodchip is another increasingly traded commodity and information is presented in a paper on its possible importance as a pathway for Agrilus species. Publishing only three times a year, the EPPO Bulletin cannot provoke the instant reactions available through other media but when we print a contribution to an important debate we are always willing to publish a considered response from a different perspective. For example the way in which sources of uncertainty are expressed, acknowledged and communicated by practitioners of Pest Risk Analysis is considered here in a paper from the USA, drawing on NAPPO guidance. Further thoughts on that subject would be most welcome; perhaps a European perspective, or even several contrasting European perspectives! Similarly, we carry a review in this issue of the benefits and limiting factors of biological assays for identification of plant viruses. It is thirty years since EPPO organised its first Conference on new methods of diagnosis in plant protection, and the debate between advocates of molecular methods and traditional identification techniques has continued ever since. During that time new methods have become established practice and fundamental research has produced more new methods. However a balance is still needed between rapid test results and an understanding of the whole organism. More contributions to that continuing debate would also be welcome.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.180 | 0.107 |
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".