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Record W1975610562 · doi:10.1002/jctb.1452

Parametric study of the factors influencing simultaneous denitrification and enhanced biological phosphorus removal

2006· article· en· W1975610562 on OpenAlexaff
Ajay Patel, Alpesh Gohil, George Nakhla

Bibliographic record

VenueJournal of Chemical Technology & Biotechnology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsWestern University
Fundersnot available
KeywordsDenitrificationAnoxic watersDenitrifying bacteriaChemistryPhosphorusEnhanced biological phosphorus removalAnaerobic exerciseBioreactorPulp and paper industryEnvironmental chemistryNitrateAcclimatizationActivated sludgeEnvironmental engineeringEnvironmental scienceNitrogenSewage treatmentBiologyEcology

Abstract

fetched live from OpenAlex

Abstract In this study, the effect of various factors such as C:N ratio, carbon source, percentage P content in the sludge influencing the simultaneous denitrification and enhanced biological phosphorus removal was investigated in batch tests on bean and tomato waste sludge from an upflow anaerobic sludge blanket reactor–anoxic/aerobic system and municipal sludge from a circulating fluidized bed bioreactor. A correlation between the change in redox potential and rate of P release was developed. Interestingly, maximum P release was observed at positive redox potential in some of the batch tests. Simultaneous denitrification and P release under anoxic conditions was observed during all the batch tests. Sludge acclimatization improved the efficiency of the sludge and proved independency of maximum specific denitrification rate and P content of sludges. The contribution of denitrifying PAOs to anoxic P uptake was determined through the denitrification control test at an initial level of PO 4 ‐P of 100–120 mg dm −3 . Copyright © 2006 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 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 score0.070
Threshold uncertainty score0.534

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 integrity0.0010.001
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 head0.008
GPT teacher head0.211
Teacher spread0.203 · 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.

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

Citations13
Published2006
Admission routes1
Has abstractyes

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