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Evaluation de la pollution générée par les lixiviats de la décharge publique de la ville de Fès

2008· article· fr· W2468328317 on OpenAlexaff
Hajer Chtioui, Fouad Khalil, Salah Souabi, Moulay Abdelazize Aboulhassan

Bibliographic record

VenueEnvironnement Ingénierie & Développement · 2008
Typearticle
Languagefr
FieldEnvironmental Science
TopicMunicipal Solid Waste Management
Canadian institutionsSAIT Polytechnic
Fundersnot available
KeywordsHumanitiesChemistryPhysicsArt

Abstract

fetched live from OpenAlex

Cette étude porte sur l'évaluation de la pollution de lixiviats produits par l'ancienne décharge de la ville de Fès. Le diagnostic de lixiviats a montré une forte pollution organique difficilement biodégradable qui évolue au cours du temps. En effet, la charge polluante produite par jour en DCO varie entre 20 et 216 kg. En outre, la concentration en NTK varie autour de 4 000 mg/l, tandis la concentration en NO3- varie autour de 80 mg/l. L'analyse des éléments métalliques a montré une importante concentration en chrome qui peut atteindre 9 mg/l, tandis que la concentration en Cu, Zn, Pb et Ni dépasse les normes de rejet. Par ailleurs, les teneurs en éléments métalliques analysées dans les sédiments prélevés à partir du même point que les lixiviats sont importantes et varient d'un point de prélèvement à l'autre. Le chrome présente des teneurs qui dépassent 1 250 μg/g, tandis que les teneurs du Pb et du Hg dépassent respectivement 760 et 4,7 μg/g. Les concentrations maximales en Cr et en Zn analysées dans le compost sont respectivement de 480 mg/g, et de 1 320 mg/g tandis que le Pb présente 110 μg/g. Ceci témoigne d'une pollution métallique des lixiviats provenant de la décharge brute qui reçoit toutes sortes de déchets, en particulier les déchets de tanneries, des margines, de textile, d'activités agroalimentaires…

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.436
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.002
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.000

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.

Opus teacher head0.023
GPT teacher head0.285
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2008
Admission routes1
Has abstractyes

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