Differences in wood decay by Heterobasidion parviporum in cloned Norway spruce (Picea abies)
Bibliographic record
Abstract
In forest breeding, growth has been used as the main selection trait in Norway spruce (Picea abies L. Karst.), whereas wood properties or resistance to pathogens have been taken as secondary traits. We aimed to investigate, in laboratory conditions, the rate of wood decay caused by Heterobasidion parviporum (Fr.) Niemelä & Korhonen (strains 5 and 7) in 20 Norway spruce clones. We also studied if, on average, growth, wood density, and fibre properties differed in the most and least decayed clones as well as from pith to bark. After 6 months of incubation, strain 7 effected significantly higher wood decay than strain 5 (mean 16.9% and 1.7%, respectively). The difference between the five most decayed and five least decayed clones by strain 7 was also statistically significant (P < 0.05). Moreover, regardless of clone or strain, the wood decay was highest near the pith and lowest near the bark, which is the opposite for wood density and fibre length and width. However, neither wood density nor fibre properties explained, statistically, the differences in average wood decay and decay from pith to bark. On the other hand, we could identify clones that simultaneously provided high wood quantity and relatively high wood density and low decay rate.
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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".