MétaCan
Menu
Back to cohort
Record W2123844863 · doi:10.1002/btpr.683

Modeling of activated sludge transient behavior induced by regulation of carbon and nitrogen metabolism

2011· article· en· W2123844863 on OpenAlexafffund
B. Lavallée, Paul Lessard, Peter A. Vanrolleghem

Bibliographic record

VenueBiotechnology Progress · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsUniversité LavalMinistère des Ressources naturelles et des ForêtsGouvernement du Québec
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsActivated sludgeTransient (computer programming)MetabolismNitrogenChemistryNitrogen cycleActivated carbonCarbon fibersEnvironmental chemistryBiochemistryEnvironmental scienceEnvironmental engineeringMaterials scienceSewage treatmentComputer scienceAdsorptionOrganic chemistry

Abstract

fetched live from OpenAlex

An experimental protocol to evaluate the structured biomass model proposed by Lavallée (Lavallée, Lessard, and Vanrolleghem, J Environ Eng Sci 2005;4:517-532) is presented. The protocol was devised to induce transient behavior and characterize the evolution of several internal biomass components. The proposed model is based on biochemical principles, and was fitted to the collected data. In these experiments, it was observed that filling the storage capacity of cells leads to special transient behavior, including a temporarily reduced metabolic activity. The model-based interpretation of the results showed that the observed transient behavior can be explained by cross-regulation of carbon and nitrogen metabolism. Hence, according to an extensive literature review, the cross-regulation of carbon and nitrogen can be used to model some observed transient behaviors and regulation of the storage process in activated sludge.

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)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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)0.0010.000

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 head0.022
GPT teacher head0.222
Teacher spread0.200 · 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

Citations0
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueBiotechnology ProgressSame topicWastewater Treatment and Nitrogen RemovalFrench-language works237,207