Differences in stem form and bark anomalies of northern red oak trees in forest stands in Canada and Germany
Bibliographic record
Abstract
Northern red oak (Quercus rubra L.) wood is valuable for a variety of applications not only in its natural distribution range in North America but also in Europe. Timber quality and stem diameter largely determine timber prices and respective uses. Silvicultural management is key to influencing tree growth and stem quality. In Germany, crop tree thinning is currently the standard treatment, while in Canada the shelterwood system is common practice. The objective of this study was to compare stem characteristics related to stem quality of northern red oaks from Canada with those from Germany to determine effects of different silvicultural treatments on stem quality. We examined stem characteristics from a total of 150 dominant northern red oaks in Canadian and German forest stands using the terrestrial laser scanning approach. Northern red oak stems in Canada (shelterwood system) were significantly straighter, whereas German stems (crop tree thinning approach) were significantly smoother on the surface and rounder on the upper parts of the stems (height 4–8 m). The number of bark anomalies decreased with increasing tree competition, indicating that competition is the main driver influencing external stem form and the occurrence or persistence of bark anomalies.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".