Influence of Four Spacings between Trees and Four Samplings Heights on Selected Wood Quality Attributes of White Spruce (Picea glauca (Moench) Voss)
Bibliographic record
Abstract
Four Picea glauca (Moench) Voss trees grown at each of four square spacing intensities between trees: 1.2 m, 1.8 m, 4.3 m, and 6.1 m in a plantation established in 1967 in the Petawawa Research Forest, Ontario, Canada (lat. 45.59° N, long. 77.25° W, elev. 168 m) and sampled at four different heights (1.3 m, 4.3 m, 7.3 m, 10.3 m) were used to study the impact of spacing between trees and sampling height on nine wood quality attributes (ring width, ring density, tracheid length, tracheid diameter, latewood proportion, intra-ring density variation, ring area, earlywood width, and latewood width). In the juvenile wood, ring width was wider and ring density higher than in the mature wood. Tracheid length was longer and tracheid diameter wider in the mature wood compared to the juvenile wood. The variation of ring density between the two wood zones was limited, and latewood proportion did not show any difference with wood zone. Sampling height induced variation in more wood quality attributes than did spacing. Except for growth rate, spacing between trees did not significantly impact wood quality attributes. Most of these variations were registered between widely different spacings.
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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 | 0.000 | 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".