PREDICTION OF TRACHEID LENGTH AND DIAMETER IN WHITE SPRUCE (PICEA GLAUCA)
Bibliographic record
Abstract
The establishment of patterns of radial and longitudinal variations and the development of models to predict the wood anatomical properties, especially from juvenile wood, are of interest for both wood industry and researchers. Linear regressions were used to predict whole-tree, breast height and mature tracheid length and diameter in white spruce ( Picea glauca (Moench) Voss) and the WBE model was used to predict the variation of tracheid diameter. Tracheid length and diameter increased from pith to bark. Tracheid length decreased, while tracheid diameter increased from apex to lower heights. Cambial age was the most important predictor of tracheid length. The final tracheid length models with either a log transformation or a third-order polynomial of cambial age explained 82% of the variation in the whole-tree tracheid length. At breast height, 83% of the variation in the whole tracheid length was explained using the juvenile value at a cambial age of 3 years. Up to 87% of the variation was explained by the model, including the average value of juvenile wood. However, mature wood tracheid length at breast height could not be predicted from juvenile wood. Distance from the apex predicted the tracheid widening in outer rings but failed to predict tracheid expansion of samples collected at fixed cambial ages. The WBE explained 86% of conduit widening in the outer rings. The sampling strategy, i.e . collecting samples longitudinally at a fixed cambial age vs. at a fixed calendar year is important in predicting tracheid diameter.
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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 | 0.003 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".