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Record W2062485509 · doi:10.1080/09593330.2015.1043353

Effect of organic matter to nitrogen ratio on membrane bioreactor performance

2015· article· en· W2062485509 on OpenAlex
Liying Hao, Baoqiang Liao

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEnvironmental Technology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicMembrane Separation Technologies
Canadian institutionsLakehead University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemical oxygen demandMembrane bioreactorNutrientEffluentMembrane foulingCarbon-to-nitrogen ratioPulp and paper industryHydraulic retention timeChemistryOrganic matterNitrogenWastewaterBioreactorEnvironmental scienceWaste managementEnvironmental engineeringFoulingMembraneOrganic chemistry

Abstract

fetched live from OpenAlex

Effect of chemical oxygen demand (COD) to nitrogen (COD:N) ratio in feed on the performance of aerobic membrane bioreactor (MBR) for treating a synthetic high-strength industrial waste water containing glucose was studied for over 370 days. The widely recommended nutrients ratio (COD:N:P = 100:5:1) is not necessary for aerobic biological industrial waste water treatment. An increased COD:N ratio from 100:5 to 100:2.5 and 100:1.8 had a limited impact on COD removal efficiency and further led to a significant improvement in membrane performance, a reduced sludge yield, and improved effluent quality in terms of residual nutrients. An increased COD:N ratio will benefit the industrial waste water treatment using MBRs by reducing membrane fouling and sludge yield, saving chemical costs, and reducing secondary pollution by nutrients addition. Optimization of nutrients usage should be conducted for specific industrial waste water streams.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.265
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.016

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 head0.216
Teacher spread0.210 · 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