Growth of first-order branches in <i>Betula platyphylla</i> saplings as related to the age, position, size, angle, and light availability of branches
Bibliographic record
Abstract
The growth of first-order branches was measured in 25 saplings of Betula platyphylla Sukatchev var. japonica Hara growing under various light conditions in northern Hokkaido, northern Japan, and the effect of age, tip height, length, and angle of branches and light availability at the branch tips on branch growth were examined. Branch growth was evaluated as the total biomass growth of current-year long shoots within a first-order branch (TBG), the number of long shoots currently produced by the first-order branch (CSN), and the mean biomass of current-year long shoots within the first-order branch (MSG). In general, TBG, CSN, and MSG were negatively dependent on branch age and positively dependent on height, length, angle (from the horizontal), and light availability of the branch. The relationships between each of TBG, CSN, and MSG and the independent variables were individual specific. The dependency of TBG, CSN, and MSG on the light availability at the branch tips was affected by the maximum light availability at the individual level, suggesting that branch growth is affected not only by branch-level resources but also by conditions at the individual level. Based on these results, two concepts for understanding branch growth, branch autonomy and correlative inhibition, were discussed, and prediction models for TBG, CSN, and MSG were presented.
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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 | 0.000 | 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 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".