Bending properties and strength grading of Norway spruce: variation within and between stands
Bibliographic record
Abstract
Current strength grading of Norway spruce (Picea abies (L.) Karst.) structural timber is only able to describe parts of the great variability in density and bending properties. This study assesses whether information about the origin of the timber can be used to predict its strength and stiffness, alone or in combination with machine strength grading. Three hundred and seventy-three boards from 45 trees sampled from three stands in eastern Norway were studied. Substantial parts of the variability of density, modulus of elasticity (MOE), and bending strength or modulus of rupture (MOR) of the boards studied were explained by origin (differences between sites, relative tree size (diameter at breast height), and longitudinal position in stem). Origin also gave a reduction in residual variance in addition to what was obtained by machine grading based on resonance frequencies. For MOR, the improvement was larger than what was obtained by adding density, whereas for MOE, the density was more important than information about origin.
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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 | 0.001 | 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".