Variation in Trembling Aspen and White Spruce Wood Quality Grown in Mixed and Single Species Stands in the Boreal Mixedwood Forest
Bibliographic record
Abstract
The Canadian boreal forest is largely represented by mixed wood forests of white spruce (Picea glauca (Moench) Voss) and trembling aspen (Populus tremuloides Michx). In this study, a total of 300 trees originating from three sites composed of trembling aspen and white spruce with varying compositions were investigated for wood quality traits: one site was composed mainly of aspen, one mainly of spruce and a third was a mixed site. Four wood quality traits were examined: wood density, microfibril angle (MFA), fibre characteristics, and cell wall chemistry. Social classes were also determined for each site in an attempt to provide a more in-depth comparison. Wood density showed little variation among sites for both species, with only significant differences occurring between social classes. The aspen site showed statistically lower MFAs than the aspen from the mixed site, however, no differences were observed when comparing spruce. Fibre characteristics were higher in the pure species sites for both species. There were no differences in carbohydrate contents across sites, while lignin content varied. Overall, the use of social classes did not refine the characterization of 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".