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Record W2558994203 · doi:10.2166/wst.2016.551

Sludge reduction via biodegradation of the endogenous residue (XE): experimental verification and modeling

2016· article· en· W2558994203 on OpenAlexaff
C. Fall, E. Millán-Lagunas, Carlos M. López-Vázquez, Christine M. Hooijmans, Yves Comeau

Bibliographic record

VenueWater Science & Technology · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsPolytechnique Montréal
FundersConsejo Nacional de Ciencia y Tecnología
KeywordsActivated sludgeBiodegradationActivated sludge modelDegradation (telecommunications)Residue (chemistry)ChemistryVolume (thermodynamics)WastewaterYield (engineering)Environmental scienceProcess (computing)Environmental engineeringWaste managementPulp and paper industryMaterials scienceEngineeringPhysicsComputer scienceThermodynamics

Abstract

fetched live from OpenAlex

The feasibility of sludge reduction via the XE biodegradation process was explored both experimentally and through modeling, where the main focus was on determining the value of the bE parameter (first order degradation of XE) from a continuous process. Two activated sludge (AS) systems (30 L) were operated in parallel with synthetic wastewater during 16 months: a conventional activated sludge (CAS) system and a modified low-sludge production activated sludge (LSP-AS) process equipped with a side-stream digester unit (DU). First, the long term data of the CAS reactor (1 year) were used to calibrate the ASM model and to estimate the heterotrophic decay constant of the cultivated sludge (bH = 0.29 d−1, death-regeneration basis). Second, pre-simulations were performed to design the LSP-AS system and to estimate the DU volume required (40 L), to avoid XE accumulation in the process. Third, the LSP-AS process was built, put in operation and monitored for more than 9 months. This allowed assessment of the actual behavior of the quasi-complete solids retention system. Once calibrated, the modified AS model estimated the value of the bE parameter to be in the range of 0.003–0.006 d−1, satisfactorily describing the overall sludge yield reduction of up to 49% observed in the experiments.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.020
GPT teacher head0.216
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations5
Published2016
Admission routes1
Has abstractyes

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