Wood-density variation of Norway spruce in relation to nutrient optimization and fibre dimensions
Bibliographic record
Abstract
The effect of fertilization on wood density, fibre length, fibre diameter, lumen diameter, proportion of cell wall area, and cell wall thickness of Norway spruce (Picea abies (L.) Karst.) were studied in a nutrient optimization experiment in northern Sweden. On the fertilized plots, all essential macronutrients and micronutrients were supplied in irrigation water every second day during the growing season. After 12 years' treatment, data were collected from 24 trees (40 years old) on the fertilized and control plots. Fertilization increased radial growth more than threefold, especially earlywood width, and decreased wood density by over 20% at 1.3 and 4 m height. The decrease in wood density was closely related to the proportion of latewood. The absolute wood density also decreased across the whole annual ring but proportionately more in latewood than in earlywood. A close relationship was found between the wood density and fibre properties, especially with the proportion of cell wall in a cross section of each annual ring, as well as with fibre and lumen width. The absolute cell wall thickness was clearly less related to wood density. However, rather large variations were found between individual trees in the relationship between wood density and fibre properties.
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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".