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Record W2331515190 · doi:10.2166/wst.2001.0727

Comparison of static and dynamic disinfection models for bacteria and viruses in water of varying quality

2001· article· en· W2331515190 on OpenAlexaff
Susan Springthorpe, M. Sander, Kevin Nolan, Syed A. Sattar

Bibliographic record

VenueWater Science & Technology · 2001
Typearticle
Languageen
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsUniversity of Ottawa
FundersAmerican Water Works Association Research FoundationWater Research Foundation
KeywordsDisinfectantChloramineChlorineEnvironmental scienceIndicator bacteriaWater qualityWater treatmentPulp and paper industryMicrobiologyChemistryEnvironmental engineeringFecal coliformBiologyEcology

Abstract

fetched live from OpenAlex

Disinfection studies rarely use natural waters due to demands exerted on the applied disinfectants and lack of consistent disinfectant residuals. This study compared the degree of disinfection achieved in natural waters between conventional batch (static) models and a system of similar volume where disinfectant residuals were maintained at constant levels (dynamic). In the latter, disinfectant was delivered through a hollow fibre cartridge from a slipstream of a full-scale (chloramine) or pilot (chlorine) water treatment plant. The test organisms (hepatitis A virus, poliovirus, MS-2, Mycobacterium terrae and Enterococcus durans) were selected with different resistance to the disinfectants. In general, for water of "good" quality, the differences between the two systems were often small or not apparent for monochloramine. However, for low chlorine residuals, or when additional demand was placed on the disinfectant, differences between the two systems became more apparent. Little difference was seen between disinfection of the test organisms singly or in mixtures, but injury of vegetative bacteria with monochloramine was very apparent. This system could be useful for understanding the fluctuations in disinfection efficacy that may occur in source water of varying quality, or in distribution systems, as disinfectant residuals decline.

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 score0.130
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
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 head0.078
GPT teacher head0.425
Teacher spread0.347 · 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

Citations9
Published2001
Admission routes1
Has abstractyes

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