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Record W2063747917 · doi:10.2166/wst.2009.625

Nutrient removal in an electrically enhanced membrane bioreactor

2009· article· en· W2063747917 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWater Science & Technology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsConcordia UniversityUniversity of Manitoba
Fundersnot available
KeywordsMembrane bioreactorBioreactorMembraneWaste managementChemistryEnvironmental scienceEngineeringBiochemistry

Abstract

fetched live from OpenAlex

Integration of the membrane bioreactor (MBR) into wastewater treatment facilities has gained popularity in recent years due to increasingly stringent discharge permits. However, up to now no research has been conducted on the combination of nitrification, denitrification and electrochemical phosphorus removal into a MBR system. In this study a novel electrically enhanced MBR (EMBR) system was used. Without pH adjustment and external carbon source supplementation, using synthetic feed, ammonium-nitrogen was completely eliminated; COD, total nitrogen and ortho-phosphorus were removed by 94.3%, 77% and 86.6%, respectively. The power consumption was 0.22 kW/m(3) of the influent synthetic wastewater. With a control MBR run in parallel, the applied voltage gradient of 1.82 V/cm did not exhibit adverse influence on the microbial growth. This system has the potential to achieve phosphorus removal through alternating the direct current intensity.

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.

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 score0.010
Threshold uncertainty score0.622

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.007
GPT teacher head0.224
Teacher spread0.217 · 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