Tree and stand characteristics associated with the occurrence of false heartwood in individual Japanese white birch trees
Bibliographic record
Abstract
New wood uses of Japanese white birch ( Betula platyphylla var. japonica) have attracted much attention in recent years, but false heartwood has led to a decline in commercial value due to its irregular wood color. In this study, we assessed the occurrence of false heartwood and its proportion to stem cross-sectional area (PFH) in individual Japanese white birch (482 trees) in a ca. 70-year-old natural secondary forest. Specifically, we investigated the relative strength of the direct/indirect effects of individual size (BA), growth rate (GR), crown ratio (CR), number of branch scars (NBS), basal area sum of neighboring trees (BAS) and topographic wetness index (TWI) on PFH. In total, 80.3% of trees had false heartwood. CR was found to be the most important factor, acting through direct and indirect negative effects. BA and NBS had a positive effect, and TWI had a negative effect on PFH. BA had a positive correlation with tree age, indicating that PFH can be reduced in trees with faster growth. Simultaneously, BAS had an indirect positive effect on PFH. These results suggested that thinning, which reduces BAS and increases CR, can reduce false heartwood.
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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 | 0.000 | 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) | 0.001 | 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".