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Record W2094886986 · doi:10.1139/s06-015

Performances d'un biofiltre à garnissage plastique pour le traitement d'effluents fortement contaminés en phénol, cadmium et chrome

2006· article· en· W2094886986 on OpenAlexvenueno aff
Fatiha Zidane, Bouchra Berrada, Brahim Lekhlif, M. Lounès, Jean‐François Blais

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicConstructed Wetlands for Wastewater Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsEffluentBiofilterCadmiumPhenolChromiumChemistryWastewaterChemical oxygen demandPulp and paper industryNuclear chemistryEnvironmental chemistryEnvironmental engineeringEnvironmental scienceOrganic chemistry

Abstract

fetched live from OpenAlex

The presence in domestic wastewater of high concentrations of organic and inorganic contaminants represents a serious problem for the treatment of these effluents. This research aimed to establish the performance of an aerobic biofiltration system with plastic packing for the treatment of effluents having high concentrations of phenol (300–500 mg·L –1 ), Cd(II) (2.5–10.0 mg·L –1 ), and Cr(III) (5.0–20.0 mg·L –1 ). Six biofilter units were first started in batch mode and then operated in continuous mode under similar conditions. High removal yields were measured for chemical oxygen demand (98.3% ± 0.3%), phenol (100% ± 0%), Cr (99.3% ± 0.6%), and Cd (90.4% ± 0.8%) from a synthetic effluent initially containing 300 mg·L –1 phenol, 5.0 mg Cr·L –1 , and 2.5 mg Cd·L –1 . Thereafter, the six columns were submitted to various operating conditions (hydraulic load, pH, phenol, cadmium, and chromium concentrations). This study showed that this system is efficient for the treatment of effluents having high concentrations of contaminants. To preserve a good efficiency of the system, the affluent must be kept at pH values equal to or higher than 6.0. Key words: biofiltration, phenol, chromium, cadmium, column, effluent, biomass, plastic. [Journal translation]

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.787
Threshold uncertainty score0.764

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.003
GPT teacher head0.177
Teacher spread0.175 · 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.

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

Citations3
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Environmental Engineering and ScienceSame topicConstructed Wetlands for Wastewater TreatmentFrench-language works237,207