MétaCan
Menu
Back to cohort
Record W1994197114 · doi:10.1002/jctb.1679

Assessing chemical oxygen demand and nitrogen conversions in a multi‐stage activated sludge plant with alternating aeration

2007· article· en· W1994197114 on OpenAlexaff
Paul Lessard, Marie‐Hélène Tusseau‐Vuillemin, A. Héduit, Fabienne Lagarde

Bibliographic record

VenueJournal of Chemical Technology & Biotechnology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsAnoxic watersAerationActivated sludgeChemical oxygen demandDenitrificationMass transferNitrogenChemistryActivated sludge modelEnvironmental engineeringMixed liquor suspended solidsEnvironmental scienceWaste managementOxygenPulp and paper industrySewage treatmentEnvironmental chemistryEngineeringChromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract This paper provides a detailed investigation of the mass transfers involved in chemical oxygen demand (COD) and N removal in an intermittent aeration activated sludge plant, as described by the widely used ASM1 model. The model was calibrated and validated on a data set obtained during three intensive sampling campaigns. The mass transfers of COD and nitrogen were calculated with the calibrated model for every biodegradable variable of the model in each tank of the biological treatment. Only by making this balance can evaluation of the contribution of each reactor (anaerobic, anoxic and intermittently aerated) to carbon and nitrogen removal be done. It was pointed out that in such a plant (activated sludge under very low organic mass loading (F/M) ratios, sludge retention time of 30 days) operating at 20 °C, the contribution of the anoxic tank in the denitrification process is very low (only 17%). The oxygen transfer in this tank was also estimated and found partly responsible for the low denitrification efficiency. Copyright © 2007 Society of Chemical Industry

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

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)0.0000.000

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 head0.017
GPT teacher head0.259
Teacher spread0.242 · 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 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

Citations7
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Chemical Technology & BiotechnologySame topicWastewater Treatment and Nitrogen RemovalFrench-language works237,207