Phenotypic Correlations among Growth and Selected Wood Properties in White Spruce (Picea glauca (Moench) Voss) †
Bibliographic record
Abstract
We examined phenotypic relationships among radial growth-related, physical (i.e., related to wood density), and anatomical (i.e., related to tracheid dimensions) wood properties in white spruce (Picea glauca (Moench) Voss), in order to determine the strength and significance of their correlations. Additionally, principal component analysis (PCA) was used to establish if all of the properties must be measured and to determine the key properties that can be used as proxies for the other variables. Radial growth-related and physical properties were measured with an X-ray densitometer, while anatomical properties were measured with a Fiber Quality Analyzer. Fifteen wood properties (tracheid length (TL) and diameter (TD), earlywood tracheid length (ETL) and diameter (ETD), latewood tracheid length (LTL) and diameter (LTD), ring width (RW), ring area (RA), earlywood width (EWW), latewood width (LWW), latewood proportion (LWP), ring density (RD), intra-ring density variation, earlywood density (EWD), and latewood density (LWD)) were assessed. Relationships were evaluated at intra-ring and inter-ring levels in the juvenile wood (JW) and mature wood (MW) zones. Except for a few cases when mature tracheid diameter (TD) was involved, all intra-ring anatomical properties were highly and significantly correlated. Radial growth properties were correlated, with stronger relationships in MW compared to JW. Physical properties were often positively and significantly correlated in both JW and MW. A higher earlywood density coupled with a lower latewood density favored wood uniformity, i.e., the homogeneity of ring density within a growth ring. Managing plantations to suppress trees growth during JW formation, and enhancing radial growth when MW formation starts will favor overall wood quality. In order, RW-EWW-RA, TL-ETL-LTL, and RD-EWD-LWP are the three clusters that appeared in the three wood zones, the whole pith-to-bark radial section, the juvenile wood zone, and the mature wood zone.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".