Modeling the Transition from Juvenile to Mature Wood Using Modulus of Elasticity in Lodgepole Pine
Bibliographic record
Abstract
The transition of modulus of elasticity (MOE) values from juvenile to mature wood marks the change between variable, low-quality wood to wood that is stronger and more consistent. Knowing the proportion of mature wood in a log can lower processing costs and allow for higher-quality products. We measured MOE in breast height pith-to-bark samples from lodgepole pine (Pinus contorta) trees in six sites in Alberta and British Columbia, Canada. We assessed eight different two-segment regression models (a first linear, quadratic, exponential or power segment, and a second linear or constant segment) to determine the transition point from juvenile to mature wood based on MOE. All eight models provided useful and significant estimates of the transition point. For the first segment (juvenile phase), the quadratic form predicted the latest transition to mature wood, the exponential form predicted the earliest transition, and the linear and power forms were intermediate. Use of a linear form for the second segment (mature phase) provided only a minor improvement over use of a constant. There were significant differences in transition point based on MOE among some of the sites, and correlations between transition points and tree diameter or height were found at two of the six sites.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".