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Record W2921969207 · doi:10.2166/wqrj.2000.013

Effect of Additives on Biological Treatment of Landfill Leachate

2000· article· en· W2921969207 on OpenAlexaffabout
Julie-Marie Pouliot, Ernest K. Yanful, Amarjeet Bassi

Bibliographic record

VenueWater Quality Research Journal · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsWestern University
Fundersnot available
KeywordsLeachatePhosphoric acidEffluentChemistryPolyethyleniminePulp and paper industryEnvironmental chemistryChemical oxygen demandWaste managementEnvironmental scienceEnvironmental engineeringWastewaterOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Aerobic batch bioreactors were used in this research to study the effects of different additives on the biological treatment of landfill leachate. Those additives were phosphoric acid, powdered activated carbon, polyethylenimine and BOD Balance™. Both synthetic and natural landfill leachates were investigated. The natural leachate was collected at a landfill site near London, Ontario. It was observed that the addition of phosphoric acid increased the COD utilization rate as well as decreased the effluent COD. The other additives did not affect the effluent COD but were found to have a small influence on the COD utilization rates, especially PEI and BOD Balance. A maximum average COD utilization rate of 90 mg L-1 h-1 was obtained with the following combination of additives: phosphoric acid and BOD Balance at 5 mg L-1.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.443
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0130.001

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 head0.103
GPT teacher head0.391
Teacher spread0.288 · 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

Citations2
Published2000
Admission routes2
Has abstractyes

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