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Record W2022551092 · doi:10.1080/10934529.2012.660093

Quantitative bacteriological assessment of aerobic wastewater treatment quality and plant performance

2012· article· en· W2022551092 on OpenAlexafffund
Behrooz Razban, Kristina Y. Nelson, D. Roy Cullimore, Jason Cullimore, Dena W. McMartin

Bibliographic record

VenueJournal of Environmental Science and Health Part A · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Nitrogen Removal
Canadian institutionsUniversity of Regina
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsEffluentWastewaterSewage treatmentAerobic bacteriaSecondary treatmentEnvironmental sciencePopulationEnvironmental engineeringHeterotrophPulp and paper industryBacteriaBiologyEngineeringMedicine

Abstract

fetched live from OpenAlex

The application of a novel method for measuring changes in defined bacterial populations during aerobic wastewater treatment was investigated. Changes in bacterial communities and total active cells can be used as surrogates for identifying potential WWTP treatment train efficiency and operational performance malfunctions. In this study, the quantities of active heterotrophic aerobic bacteria (HAB) in weekly wastewater samples collected from twelve locations across a WWTP were determined colorimetrically using biological activity reaction tests (BART). Samples were collected for 2 months from primary, secondary and tertiary unit processes. The results show a mean HAB population decrease of 99.8% from primary influent to tertiary effluent, with the largest reductions occurring in the secondary aerobic lagoons. The results were reproducible and robust supporting the applied BART analytical method as an indicator not only of overall efficacy of the WWTP processes but also of potential WWTP process malfunctions.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.353

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.090
GPT teacher head0.351
Teacher spread0.261 · 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 designObservational
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

Citations5
Published2012
Admission routes2
Has abstractyes

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