Characterization of damage and biotic factors associated with the decline of <i>Eucalyptus wandoo</i> in southwest Western Australia
Bibliographic record
Abstract
Crown decline of wandoo, Eucalyptus wandoo, in southwest Western Australia has escalated over the last 10 years, so very few unaffected stands remain. To assess the canopy-damage characteristics of trees in decline a destructive, partial-harvest method was used to sample branches in natural mixed-age stands. Necrosis of common cankers was closely associated with type-1 borer damage, characterized by "longitudinal" gallery structure on declining trees only. Cankers were found to be consistently more severe on declining trees, with decay regions affecting a greater proportion of sapwood tissue. Several infestations causing type-1 borer damage that varied in age were found on declining branches, providing evidence of cyclical damage events. Type-2 borer damage characterized by "ring-barking" gallery structure caused extensive damage in canopies, but was not always associated with decline. Interactions between foliage density and canker score showed that 17.8% and 63.1% of the variability in foliage-density ratios was accounted for in declining intermediate-health and unhealthy classes, respectively. The relationship was negligible for the healthy class (9.9%), providing strong evidence that cankers are causing foliage loss in declining canopies. Evidence suggests that an interaction between type-1 borer infestations and decay-causing fungi is responsible for the decline in E. wandoo wandoo canopies.
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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 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".