Presence of <i>Heterobasidion</i> infections in Norway spruce stumps 6 years after treatment with <i>Phlebiopsis gigantea</i>
Bibliographic record
Abstract
Summary Natural colonization by the root and butt rot causing fungi Heterobasidion spp. on Norway spruce (Picea abies) stumps following thinning and treatment with the biological control agent Phlebiopsis gigantea was investigated on three sites in southern Sweden 6 years after treatment. The fully treated stumps and control stumps were excavated and sampled to compare the survival of Heterobasidion spp. in the long term. Six years post‐treatment, 47 and 11% of untreated and treated stumps, respectively, had Heterobasidion infection. There was no difference in the relative infected area in discs collected from the butt and the roots for the different treatments. Control efficacy was 83% for treated stumps. After 6 years, there were no apparent differences between the remaining infections in treated compared with those in untreated stumps regarding the number of colonies, their size or relative infection area. Although infections, 3 months after treatment with P. gigantea, were significantly fewer and smaller than in untreated stumps, Heterobasidion inoculum can survive for at least 6 years in the stump and, when it does, constitute a risk for neighbouring trees.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".