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In Vitro Genotoxicity of Wastewaters from the Town of Settat, Morocco

2009· article· en· W2158645688 on OpenAlexfundno aff
Jaouad El Asslouj, Loubna Amahdar, K. Glouib, Sanaê Kholtei, N. El Amrani Paaza, Luc Verschaeve, Abderraouf Hilali

Bibliographic record

VenueArchives of Industrial Hygiene and Toxicology · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCarcinogens and Genotoxicity Assessment
Canadian institutionsnot available
FundersInstitut National de la Recherche AgronomiqueInternational Development Research Centre
KeywordsGenotoxicityMicronucleus testGroundwaterMicronucleusEnvironmental sciencePollutionPeripheral bloodWastewaterToxicologyWater pollutionEnvironmental engineeringEnvironmental protectionBiologyChemistryToxicityEcologyImmunologyGeology

Abstract

fetched live from OpenAlex

In recent years, the town of Settat has seen a considerable industrial growth, which has resulted in increased environmental pollution. This includes pollution by household and industrial wastewaters, which are released into the Boumoussa River without any preliminary treatment. The river valley crosses the community of Mzamza 8 km to the north of the town. Years of drought forced members of the community to use this polluted ground water for irrigation and put themselves and the environment at risk.The aim of this study was to determine the physicochemical and metal profile of Settat wastewaters and to assess their impact on the water table. The second objective was to investigate the genotoxic potential of wastewater on human peripheral blood lymphocytes in vitro, using the micronucleus test and cellular proliferation index.This study demonstrated significant pollution of Boumoussa valley groundwater and of the local wells. Sampled water induced a clear increase in the frequency of micronucleated cells and a lower cell proliferation in human peripheral blood lymphocytes in vitro.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.250
Teacher spread0.233 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations6
Published2009
Admission routes1
Has abstractyes

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