Investigation of Shrinkage in Softwood Using Digital Image Correlation Method
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Bibliographic record
Abstract
Distortion in lumber, such as twist, cup, spring and bow, can cause serious problems for its use in service. Lumber distortion is largely a result of differential shrinkage in wood in different directions and the presence of different types of wood (i.e. juvenile and mature wood) in a single piece. Shrinkage varies within tree because of different types of wood. In this paper, the digital image correlation (DIC) method was used to investigate shrinkage variation within tree. The DIC method is an image-based, non-contact and full-field displacement and strain measurement method. Two softwood species grown in Eastern Canada, jack pine and white spruce, were used in this study. In this paper, average full-field shrinkage over each growth ring was measured, and the growth ring position in relation to pith of the tree was recorded. The shrinkage variations in the radial, tangential and longitudinal directions in a tree stem are presented. The work described in this paper is part of a larger study to develop a modeling technique to predict distortion of lumber based on its position in a tree stem.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it