Mixed Taper Equations for African Mahogany Plantations ( Khaya grandifoliola C. DC.) Near Thinning and Clear-cut Ages
Bibliographic record
Abstract
Abstract The present study aimed to develop taper equations for African mahogany trees in two important ages (near to thinning and near to clear-cut ages), using, respectively, 100 seven-year-old trees were scaled in Minas Gerais and 46 fourteen- and fifteen-year-old trees were scaled in Pará. The fifth-degree polynomial, the polynomials with integer and fractional powers, the Kozak exponential model, and the modified Kozak model were tested. The equations were assessed and, next, the inclusion of a random term in the best equation at tree level was tested. The best resulting equation was selected, and it was validated using the bootstrapping method. The Kozak exponential model and the modified Kozak model were selected, to trees near thinning and near clear-cut age, respectively. Inserting a random term at tree level in the equation improved its estimates by 5.2% and 8.9% for trees near thinning and clear-cut ages, respectively.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".