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Record W2168367824 · doi:10.1680/jees.2013.0059

Contribution à l’étude de l’effet de la coagulation avant chloration sur la formation des trihalométhanes (THM) et composés organohalogénés (COX) dans les eaux alimentant la ville de Casablanca au Maroc (in French)

2013· article· fr· W2168367824 on OpenAlexaffvenue
Fatiha Zidane, Karima Cheggari, Jean‐François Blais, Patrick Drogui, Jalila Bensaïd, Saïd Ibn Ahmed

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2013
Typearticle
Languagefr
FieldEnvironmental Science
TopicWater Treatment and Disinfection
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsForestryGeography

Abstract

fetched live from OpenAlex

Cette étude visait la détermination et le suivi des sous-produits de désinfection (SPD) halogénés des eaux naturelles servant à la production d’eau potable de la ville de Casablanca au Maroc. Dans un premier temps, un suivi des paramètres physicochimiques des eaux naturelles a été effectué dans le but de caractériser ces eaux, pour lesquelles la demande en chlore a été déterminée à partir du traçage de la courbe de point de rupture (« break point »). Dans un deuxième temps, des eaux ont été synthétisées au laboratoire, sur la base des résultats des analyses effectuées précédemment. Ces eaux synthétiques ont fait l’objet, elles aussi, de la détermination des courbes de point de rupture. Afin d’évaluer les conséquences de la chloration, des tests de suivi des trihalométhanes (THM) et des composés organohalogénés (COX), avant et après coagulation ont été effectués. Les résultats obtenus pour les eaux naturelles ont montré une corrélation entre le carbone organique total (COT), la teneur et la nature des THM et les COX formés suite à la chloration. Aussi, les résultats ont montré que la coagulation avant chloration permet de réduire la formation de SPD.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.204
Teacher spread0.198 · 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

Citations4
Published2013
Admission routes2
Has abstractyes

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Same venueJournal of Environmental Engineering and ScienceSame topicWater Treatment and DisinfectionFrench-language works237,207