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Record W2965308687 · doi:10.1002/aws2.1150

A multiple‐site field study of stabilized hydrogen peroxide for drinking water disinfection

2019· article· en· W2965308687 on OpenAlexaffabout
Yamuna S. Vadasarukkai, Xinhai Guo, Robert Tyssen, Joanna El Hares, Ludo Feyen, Steven N. Liss, Jim Shubat, Robert K. Abernethy

Bibliographic record

VenueAWWA Water Science · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Treatment and Disinfection
Canadian institutionsToronto Metropolitan UniversityQueen's UniversityOutotec (Canada)
Fundersnot available
KeywordsDisinfectantHaloacetic acidsHydrogen peroxideChlorineChemistryEnvironmental chemistryEnvironmental engineeringEnvironmental scienceOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract This study examined the impact of changing the secondary disinfectant from chlorine to a stabilized hydrogen peroxide (SHP) in three full‐scale drinking water treatment plants serving small communities in the provinces of Ontario and Newfoundland, Canada. In all three communities, the SHP residuals were maintained within the limits specified by local regulators, with the exception of one of the sites in Newfoundland, where residuals were outside these limits on several occasions during the study. Following the transition to the SHP system, total coliforms and Escherichia coli consistently tested negative (nondetected) in all cases. Switching to the SHP system reduced concentrations of total trihalomethanes to 22–44 μg/L and total haloacetic acids to 47–70 μg/L, corresponding to 72 ± 9 and 67 ± 11% reductions, respectively. The present study indicated that changing the secondary disinfectant to SHP did not negatively affect the polyvinyl chloride and ductileiron pipes in the distribution systems studied.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.484
Threshold uncertainty score0.963

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.223
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2019
Admission routes2
Has abstractyes

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