Models for predicting vertical profiles of heartwood diameter in mature Scots pine
Bibliographic record
Abstract
Variation in heartwood diameter (HWD) along the stem was studied in 106 mature Scots pines ( Pinus sylvestris L.) sampled from southern Norway. HWD decreased from the base towards the treetop, following a profile similar to that of the stem diameter (shape of the tree). A few trees deviated from this general pattern. In these trees HWD increased from the base of the stem to a maximum at 2–2.5 m and then decreased towards the top of the tree. Random coefficient mixed models based on a second-degree polynomial of vertical position in the tree and tree variables that can be measured in the forest were developed to predict HWD profiles of pine stems. Seven different models were developed in steps, based on how easily the input variables can be measured. Input variables consisted of information describing the size and shape of trees and information from increment cores. Performances of the models were validated with an independent sample (R2 = 0.88–0.95, root mean square error = 12–19 mm). The high predictive abilities of the models indicate that they can be prospective tools for selecting trees and stem sections within trees to produce logs with HWD suitable for manufacturing of heartwood sawn-wood products.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".