Modélisation du volume du fût d'arbre pour une gestion durable des écosystèmes forestiers soudaniens
Bibliographic record
Abstract
La difficulté de disposer d’un tarif de cubage de chaque essence en forêt naturelle a conduit les aménagistes à utiliser le coefficient de forme proposé par Dawkins. Cette note propose une méthode conciliant les exigences écologiques (aspect non destructif du cubage des arbres sur pied) et la mise à disposition d’outils adéquats d’estimation du volume des arbres sur pied. Trois essences ont été choisies dans la forêt classée de Wari-Maro au Bénin pour mener l’étude : Isoberlinia spp., Anogeissus leiocarpa et Daniellia oliveri. Il ressort que la meilleure équation de cubage du volume du fût est de la forme V = a + bD2 H quelle que soit l’essence. L’étude comparative révèle une amélioration de l’estimation du volume fût de l’ordre de 10 % sur le modèle de Dawkins.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".