Early development of root rot in young Norway spruce planted on sites infected by <i>Heterobasidion</i> in southern Finland
Bibliographic record
Abstract
Root rot infections in Norway spruce (Picea abies (L.) Karst.) regeneration, planted after the clear-cutting of spruce on sites infested by Heterobasidion, were investigated on 21 experimental plots in eight 2- to 23-year-old plantations. Heterobasidion root rot became evident about 10 years after planting and the proportion of infected spruces increased steadily with plantation age. The average number of planted spruces infected per old decayed stump was 0.2 trees in 2- to 9-year-old plantations, 0.8 trees in 11- to 15-year-old plantations, and 1.8 trees in 20- to 23-year-old plantations. About 10 and 20 years after planting, 7 and 23% of the planted spruces in the disease centers were infected by Heterobasidion. Heterobasidion parviporum Niemelä & Korhonen, and Heterobasidion annosum (Fr.) Bref. s. str. caused 98 and 2% of the Heterobasidion infections in the previous spruce rotation, and 96 and 4% in the spruce regeneration, respectively. In all, 71% of the infected regeneration trees were attacked by a Heterobasidion genet that was also isolated from the stumps of the previous tree stand. Armillaria species (Armillaria borealis Marxmüller & Korhonen and Armillaria cepistipes Velenovský) were isolated from 7% of the planted spruces.
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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 | 0.000 |
| 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".