Relationships between mechanical properties of oak timber (Quercus robur L.)
Bibliographic record
Abstract
Abstract Ring-porous hardwoods such as oak are in high demand for furniture-making, cooperage, flooring, and construction. However, evaluating the quality of such timber is difficult and time consuming, and simpler tests are required. Models for predicting as many mechanical properties as possible, based on easier-to-determine mechanical tests, may help. In this study, the hardness, modulus of elasticity, bending, compression, and impact bending strength parallel to grain were tested on defect-free laths obtained from a sample of 42 oak trees. The relationships between the variables were investigated. Three models that relate the resistance to axial compression with bending strength and stiffness (R 2 >0.55; P<0.01) are proposed for defect-free oak timber. Selection of models mainly depended on the bias, which was highly variable among the models tested. The prediction models proposed in the international standard EN 384:2004 for structural dimension timber are not suitable for small clear wood specimens, especially in very elastic woods. The relative independence of hardness and impact bending strength as regards the other mechanical properties is also demonstrated.
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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 | 0.001 |
| 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) | 0.001 | 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".