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Record W1976963467 · doi:10.2166/wst.2006.844

Hydrogen-driven denitrification of wastewater in an anaerobic submerged membrane bioreactor: potential for water reuse

2006· article· en· W1976963467 on OpenAlexaff
B. Rezania, Jan A. Oleszkiewicz

Bibliographic record

VenueWater Science & Technology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsEffluentDenitrificationWastewaterNitrateBioreactorWaste managementChemistryMembrane bioreactorReuseTotal organic carbonEnvironmental engineeringAnaerobic exerciseEnvironmental scienceHydrogenPulp and paper industryEnvironmental chemistryNitrogenOrganic chemistryEngineeringBiology

Abstract

fetched live from OpenAlex

An anaerobic submerged membrane bioreactor was coupled with a novel hydrogen delivery system for hydrogenotrophic denitrification of municipal final effluent containing nitrate. The biological treatment unit and hydrogen delivery unit were proven successful in removing nitrate and delivering hydrogen, respectively. Complete hydrogen transfer resulted in reducing nitrate below detectable levels at a loading of 0.14 kg Nm(-3) d(-1). The produced water met all drinking water guidelines except for color and organic carbon. However, the organic carbon was removed by 72% mostly by membrane rejection. To reduce the organic carbon and color of the effluent, post treatment of the produced water is required.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.573

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.008
GPT teacher head0.214
Teacher spread0.206 · 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

Citations8
Published2006
Admission routes1
Has abstractyes

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