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Record W2316174033 · doi:10.2166/wqrjc.2013.110

Evaluation of the adenosine triphosphate (ATP) bioluminescence assay for monitoring effluent quality and disinfection performance

2013· article· en· W2316174033 on OpenAlexaff
Natalie Linklater, Banu Örmeci

Bibliographic record

VenueWater Quality Research Journal · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicbioluminescence and chemiluminescence research
Canadian institutionsCarleton University
Fundersnot available
KeywordsEffluentChlorineWastewaterAdenosine triphosphateChemistrySewage treatmentBioluminescenceWater qualityMicroorganismPulp and paper industryEnvironmental chemistryMicrobiologyChromatographyEnvironmental scienceBacteriaBiochemistryBiologyEnvironmental engineeringEcology

Abstract

fetched live from OpenAlex

This study investigated the use of the adenosine triphosphate (ATP) bioluminescence assay as a tool for monitoring water and wastewater quality and disinfection performance subsequent to ultraviolet (UV) irradiation and chlorine disinfection. Two different commercially available ATP assays were used in the study and controlled experiments were carried out using a pure Escherichia coli culture to determine how the ATP content of samples change after they are exposed to UV and chlorine. Finally, a selected assay was used with samples collected from drinking water and wastewater treatment plants to assess its potential use by treatment plants for process and effluent monitoring. The ATP assay could detect the chlorine damage to cells but the detection limit of the assay was not sensitive enough to determine the level of chlorine disinfection performance. No clear trend was observed between UV irradiation and ATP content of the cells. Samples were also collected from water and wastewater treatment plants and a good correlation was observed between the culture-based methods and the ATP assay results, which indicate the potential use of the ATP assay as a process and effluent quality monitoring tool at treatment plants.

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)0.020
metaresearch head score (Gemma)0.002
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 score0.076
Threshold uncertainty score0.687

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.161
GPT teacher head0.438
Teacher spread0.277 · 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
Published2013
Admission routes1
Has abstractyes

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