Fuelwood production in the degraded agricultural areas of the Aral Sea Basin, Uzbekistan
Bibliographic record
Abstract
Les petites plantations installees a des fins de phyto-remediation dans des parcelles degradees du bassin de la mer d'Aral (Asie centrale) sont des sources potentielles d'energie pour les menages ruraux, souvent sans acces au gaz. Des donnees sur les caracteristiques energetiques des essences locales sont indispensables pour la selection d'essences destinees au boisement de parcelles marginales. Les proprietes energetiques - densite, cendres et valeur calorifique (indice energetique du bois de feu, Fvi), rapport biomasse-cendres, humidite, carbone, azote - ont ete etudiees dans le bois de Elaeagnus angustifolia, Ulmus pumila et Populus euphratica, pendant quatre ans. Les valeurs calorifiques du bois de fut sont assez stables : 19,0-19,2 MJ kg -1 pour E. angustifolia, 18,2-19,0 pour U. pumila et 18,3-19,3 pour P. euphratica. La densite du bois variait de 0,44 a 0,57 g cm- 3 , et les cendres entre 0,6 et 11 % en raison de la salinite elevee. Les cendres sont la caracteristique la plus decisive pour la chaleur de combustion, comme l'indique sa relation inverse aux valeurs calorifiques (r 2 = 0,77). Il n'existe pas de correlation entre valeur calorifique et densite du bois (r 2 = 0,02). En termes de Fvi, les essences se classaient: E. Angustifolia > U. pumila > P. euphratica. Apres quatre ans, la valeur energetique d'un hectare d'arbres plantes avec 2 300 tiges ha -1 suivait l'ordre: P. euphratica (10,3 t equivalent petrole, tep), E. angustifolia (8,4 tep), U. pumila (6,4 tep), informant sur l'energie equivalente potentielle des plantations d'arbres dans les terres marginales.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 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".