Variation of Wood Density in Tropical Rainforest Trees
Bibliographic record
Abstract
Measurement of wood density in Congo Basin forests are needed to reduce uncertainties on estimations of carbon stocks. The purpose of this study was to test vertical variation and temperature variation (80 °C, 105 °C) effects on wood density of species in a semi-deciduous forest of eastern Cameroon. Wood samples were collected on felled trees, at the base, middle of the trunk and on the branches in plots of 10 m x 10 m for trees <5 cm diameter, of 20 m x 10 m for trees with diameter between 5 and 10 cm and, of 20 m x 250 m for trees with diameter ≥ 10 cm. 162 trees with diameter between 1 cm and 146 cm were used. The highest wood density (0.912) was found in Ficus sp. and lowest (0.295) in Enantia chlorantha. Using 80 °C as temperature to estimate wood density increased the value of about 10% when compare to the reference temperature of 105 °C. A significant difference was observed between wood density of the base and the top of trees studied. 10 species did not have wood density reported in the Global Wood Density database. This study recommends further research on wood density to cover as many tree species as possible in the Congo Basin.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".