Influence of brushing frequency on birch population structure after felling
Bibliographic record
Abstract
:Populations of Betula pendula and Betula pubescens in felling stands subject to different brushing regimes were studied in the southern taiga forest (Tsentralno-Lesnoi Biosphere Zapovednik, Russia). The stands are 14- and 20 y old and are situated in the Oxalis type of spruce forest. The number of birch saplings, the height and ontogenetic stage (reflecting the biological age) of individual saplings in the community were determined in ten 5- × 10-m plots, five in a 14-y-old stand that had undergone a single brushing event and five in a 20-y-old stand that had undergone three (regular) cleanings. In the 14-y-old stand, birches were more numerous (the total number of birch saplings was 10,800.0 ± 1365.3 stems∙ha-1), saplings were higher (B. pendula: 2.59 ± 0.08 m; B. pubescens: 1.80 ± 0.12 m), and populations were more mature (most B. pendula saplings had changed to tree stage v from bush stage im). The total number of saplings in the 20-y-old stand was 1120.0 ± 338.2 stems∙ha-1, the mean height of B. pendula was 2.47 ± 0.45 m, the mean height of B. pubescens was 1.45 ± 0.14 m, and saplings in immature stages dominated. Natural forest regeneration was dominated by B. pendula, which was almost twice as abundant as B. pubescens in the 20-y-old stand, and three times more abundant in the 14-y-old stand.
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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 | 0.000 | 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 | 0.000 |
| 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 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".