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Record W2057335350 · doi:10.1080/09593331003710228

Extraction of nutrients from foam in a membrane activated sludge system

2010· article· en· W2057335350 on OpenAlexaff
K.V. Lo, W.I. Chan, Ing W. Lo, F. T. Koch, Ping Liao

Bibliographic record

VenueEnvironmental Technology · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicPhosphorus and nutrient management
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsActivated sludgeMembraneNutrientChemistryExtraction (chemistry)Waste managementChromatographyPulp and paper industryChemical engineeringEnvironmental scienceEnvironmental engineeringSewage treatmentEngineeringBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

This study investigated the feasibility of treating the foams generated in enhanced biological phosphorus removal processes with the microwave-enhanced advanced oxidation process to reduce solids and solubilize nutrients for recovery purposes. It was found that more than half of the total chemical oxygen demand was solubilized during the treatment with just a small dose of hydrogen peroxide, signifying effective destruction of foam solids. Significant solubilization of phosphates, volatile fatty acids and ammonia was also observed, along with the release of metals contained in the foam, including calcium, potassium, and magnesium, which thereby represents additional potential benefits for nutrient recovery via subsequent crystallization processes. Since the solids content of foam is typically high, pretreatment for thickening sludge solids is not necessary prior to the use of microwave-enhanced advanced oxidation processes. As a result, this also offers further potential for reduction of energy costs. The process could be an efficient method for the removal and control of foam and the recovery of all available phosphorus at the same time.

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 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 score0.019
Threshold uncertainty score1.000

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.003
GPT teacher head0.191
Teacher spread0.188 · 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
Published2010
Admission routes1
Has abstractyes

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