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Record W1984440574 · doi:10.1080/09593332308618387

Récupération du Plomb et du Zinc par Adsorption sur Tourbe Lors de La Décontamination de Chaux Usées D'incinérateur de Déchets Municipaux Lead and Zinc Recovery by Adsorption on Peat Moss During Municipal Incinerator Used Lime Decontamination

2002· article· fr· W1984440574 on OpenAlexaff
J. F. Blais, Guy Mercier, Alexis Durand

Bibliographic record

VenueEnvironmental Technology · 2002
Typearticle
Languagefr
FieldEnvironmental Science
TopicAdsorption and biosorption for pollutant removal
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsZincEnvironmental scienceChemistryEnvironmental chemistryEnvironmental engineering

Abstract

fetched live from OpenAlex

The objective of this research was to evaluate the efficiency of peat moss for lead and Zn recovery from alkaline leachates (pH 11.5) produced during decontamination of municipal incinerator fly ash. Tests carried out with peat moss columns (density of 0.13 g m l(-1)) gave very high removal yields for lead (98.9 to 100%) and Zn (98.4 to 99.8 %). The initial metal concentrations in the leachates were 126 to 138 mg Pb l(-1) and 14.4 to 23.5 mg Zn l(-1). The columns were fed using two rates (20 and 40 ml min(-1)), which correspond respectively to 17.6 and 8.8 min as contact time on peat moss. Adsorption efficiencies of 16 to 18 mg Pb g(-1) and 1.7 to 3.2 mg Zn g(-1) have been measured during this fly ash leachate treatment study. The adsorbed toxic metals can be desorbed using a chlorhydric acid solution. The peat moss can be regenerated and reused for several adsorption cycles without loss of the lead and Zn adsorption efficiencies.

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 categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
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 score0.401
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.009
GPT teacher head0.213
Teacher spread0.204 · 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 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

Citations10
Published2002
Admission routes1
Has abstractyes

Explore more

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