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Record W2320687160 · doi:10.2166/wst.2012.629

Modelling the degradation of endogenous residue and ‘unbiodegradable’ influent organic suspended solids to predict sludge production

2013· article· en· W2320687160 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueWater Science & Technology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsEnviroSim (Canada)Polytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMixed liquor suspended solidsVolatile suspended solidsDegradation (telecommunications)Membrane bioreactorSuspended solidsWastewaterActivated sludgeEnvironmental scienceEnvironmental engineeringPulp and paper industryChemistryBioreactorSewage treatmentActivated sludge modelWaste managementEngineering

Abstract

fetched live from OpenAlex

Activated sludge models have assumed that a portion of organic solids in municipal wastewater influent is unbiodegradable. Also, it is assumed that solids from biomass decay cannot be degraded further. The paper evaluates these assumptions based on data from systems operating at higher than typical sludge retention times (SRTs), including membrane bioreactor systems with total solids retention (no intentional sludge wastage). Data from over 30 references and with SRTs of up to 400 d were analysed. A modified model that considers the possible degradation of the two components is proposed. First order degradation rates of approximately 0.007 d(-1) for both components appear to improve sludge production estimates. Factors possibly influencing these degradation rates such as wastewater characteristics and bioavailability are discussed.

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 score0.006
Threshold uncertainty score0.366

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.016
GPT teacher head0.198
Teacher spread0.182 · 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