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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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 teacher head, 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".