Regional variation in wood modulus of elasticity (stiffness) and modulus of rupture (strength) of planted loblolly pine in the United States
Bibliographic record
Abstract
Modulus of elasticity (MOE), modulus of rupture (MOR), and specific gravity (SG) are important properties for determining the end-use and value of a piece of lumber. This study addressed the variation in MOE, MOR, and SG with physiographic region, tree height, and wood type. Properties were measured from two static bending samples (dimensions 25.4 mm × 25.4 mm × 406.4 mm) representing each wood type (corewood and outerwood) at heights 2.4, 7.3, and 12.2 m from three trees sampled from 135 loblolly pine ( Pinus taeda L.) stands distributed across the natural range of the species. An analysis of variance was conducted to detect the effect of physiographpic region, height, and wood type on each property. Significant regional variation was observed for MOE, MOR, and SG for both wood types with high values in the Gulf and South Atlantic Coastal Plains compared with other regions. A significant height-related trend in MOE, MOR, and SG within a tree was identified; MOE and MOR increased in corewood and decreased in outerwood with height. Maps showing regional variation in MOE and MOR at different heights by wood type were produced and showed significant variation for both 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".