Bibliographic record
Abstract
Tree branches provide multiple functions in tree growth. It is necessary to study the allometric patterns of branches in order to understand some quantitative perspectives in tree growth. In this study, branches of seven crape myrtle trees (Lagerstroemia indica) were studied to examine allometric relationships in different times. The results indicated that the total basal area of branches at one order was far more than it at the next lower order (branches far from trunks). The scaling exponents of frequency distribution in both branch length and diameter decreased from above 1.0 in May to 0.1 in November as branches grew. The entropy of branch length and diameter both decreased at the beginning and then increased for all trees during the growing season. The observed entropy was always less than the maximum entropy. The average slenderness of branches was close to 20 for all trees. There were higher fluctuations in the slenderness within small or short branches (diameter less than 10 mm or length less than 100 cm). The scaling exponents between branch radius and length were concentrated at 1.0 for most trees. The correlation between the branch diameters of 1st order and the number of branches at 2nd order was not significant. The general trend and deviations in allometric relationships may help to understand the complexity in tree branch development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.000 | 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".