The effect of winter thinning on the spread of <i>Heterobasidion parviporum</i> in Norway spruce stands
Bibliographic record
Abstract
Genets of Heterobasidion were identified in eight 43- to 56-year-old Norway spruce ( Picea abies (L.) Karst.) stands in southern Finland. Four of the stands had been thinned in winter ca. 10 years prior to the study, and four had been left unthinned. It was hypothesized that the felling of decayed trees promotes the vegetative spread of the fungus from thinning stumps into the adjacent trees, and hence the Heterobasidion genets should be larger in thinned stands. Although the number of infected stumps per areal unit was lower and the genets were slightly smaller in the previous tree generation of thinned plots, the genets, particularly the old ones, in the present tree generation were larger on thinned plots. The genets originating from the previous rotation included, on average, 12.2 trees on thinned plots and 6.7 trees on unthinned plots. The mean number of trees infected by new genets (not found in previous generation) was also slightly higher (p < 0.05) on thinned than on unthinned plots, 1.8 and 1.2 trees, respectively. The results indicate that the rapid expansion of old Heterobasidion infections after a thinning operation may significantly contribute to the occurrence of root rot in the residual stand.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".