Within-tree patterns of wood stiffness for white spruce (<i>Picea glauca</i>) and trembling aspen (<i>Populus tremuloides</i>)
Bibliographic record
Abstract
Radial patterns of modulus of elasticity (MOE) were examined for white spruce (Picea glauca (Moench) Voss) and trembling aspen (Populus tremuoides Michx.) from 19 mature, uneven-aged stands in the boreal mixedwood region of northern Alberta, Canada. The main objectives were to (1) evaluate the relationship between pith-to-bark changes in MOE and cambial age or distance from pith; (2) develop species-specific models to predict pith-to-bark changes in MOE; and (3) to test the influences of radial growth, relative vertical height, and tree slenderness (tree height/DBH) on MOE. For both species, cambial age was selected as the best explanatory variable with which to build pith-to-bark models of MOE. For white spruce and trembling aspen, the final nonlinear mixed-effect models indicated that an augmented rate of increase in MOE occurred with increasing vertical position within the tree. For white spruce trees, radial growth and slenderness were found to positively influence maximum estimated MOE. For trembling aspen, there was no apparent effect of vertical position or radial growth on maximum MOE. The results shed light on potential drivers of radial patterns of MOE and will be useful in guiding silvicultural prescriptions.
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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) | 0.001 | 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".