Fungal and nematode threats to Australian forests and amenity trees from importation of wood and wood products <sup>1</sup>
Bibliographic record
Abstract
A combination of geographical isolation and effective quarantine practices has excluded many serious pathogens of trees from Australia. The international trade in untreated wood and wood products, including dunnage, has increased the likelihood of the introduction of exotic pathogens and decay fungi and their becoming established and deleteriously affecting the current relatively healthy status of Australia's native and plantation forests, and amenity trees. Forest pathogens such as Heterobasidion annosum, Fusarium circinatum, Bursaphelenchus xylophilus, Puccinia psidii, and Phellinus pini are considered serious threats to plantation forests in Australia. The potential impact, if the more serious exotic pathogens of forests were to be introduced, would not only be the loss of a few seasons' crops, but also the loss of decades of effort and investment in plantations, as well as irreparable damage to the native biota and wood resources. Effective quarantine policies and procedures are necessary to prevent the entry of these pathogens into Australia.Key words: quarantine, wood, fungal pathogens, nematodes, risk.
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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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".