Valorisation des matières résiduelles et de la biomasse forestière au Maroc : Compostage et confection de substrats organiques pour la production de plants forestiers
Bibliographic record
Abstract
The objective of this article is to describe a meth od of composting residual forest material. Four typ es of forest materials were composted (cones of Cedrus atlantica and green biomass residu es: leaves and branches of Quercus rotundifolia and Acacia mollissima as well as needled branches of Pinus halepensis). Net differen ces in the physico-chemical properties and temperat ure profiles were observed among the four types of compost. These differences are cl osely related to the nature of the material used fo r composting, the C/N ratio, the moisture content and the oxygen demand of the compost. Composting time was significantly reduced in comparison to previous studies. The physico-chemical properties of the compost are significantly better than to the forest soil. Withi n the context of the preliminary test, the results are strongly encouraging with respect t o the use of different composts to produce oak seed lings of high morpho-physiological quality.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".