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Record W2029705687 · doi:10.2166/wst.2006.366

An evaluation of full-scale activated sludge dynamics using microbial fatty acid analysis

2006· article· en· W2029705687 on OpenAlexfundaboutno aff
Alan Werker

Bibliographic record

VenueWater Science & Technology · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsActivated sludgeSewage treatmentBiomass (ecology)WastewaterMicrobial population biologyEnvironmental scienceCommunity structureSettlingPopulationWaste managementDynamics (music)Full scaleEnvironmental engineeringPulp and paper industryEcologyBiologyEngineering

Abstract

fetched live from OpenAlex

Patterns of microbial fatty acids (MFAs) from activated sludge samples were analyzed over one year's operation at the Hamilton Woodward municipal wastewater treatment plant in Canada. The objective was to examine community structure dynamics and to consider the potential for interrelationships between the population dynamics and treatment performance. With the exception of a higher than normal solids discharge on one day, the treatment plant operations were otherwise stable during the year. As such, wastewater temperature appeared to be the dominant influence on the observed dynamics of the MFA community structure. MFA monitoring and analysis was demonstrated as a practical diagnostic tool in community structure trend monitoring. While the findings did suggest potential for full-scale treatment process monitoring, further development is required. Advancement in technique and greater insight for the data interpretation will be made with historical data from continued case studies. In future studies, selective sub-sampling of biomass fractions (settling and dispersed fauna), evolution in the compositional analysis methods, and, ideally, complementary genotypic and classical microscopic analyses on select samples are recommended.

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)0.001
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 score0.065
Threshold uncertainty score0.490

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
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 head0.012
GPT teacher head0.246
Teacher spread0.234 · 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

Citations14
Published2006
Admission routes2
Has abstractyes

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