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Record W3158857011

Ion Chromatographic Analysis of Swimming Pool Water Disinfected by Ozone and Sodium Hypochlorite

2000· article· en· W3158857011 on OpenAlexaff
W.F. Mok, R. Prasad, P. Li

Bibliographic record

VenueSSRN Electronic Journal · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Treatment and Disinfection
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsHypochloriteBromateChemistrySodium hypochloriteNitrateFluorideSulfateChloramineOzoneNitriteChlorideEnvironmental chemistryIon chromatographyChlorateWater treatmentInorganic chemistryChlorineChromatographyEnvironmental engineeringBromideEnvironmental science
DOInot available

Abstract

fetched live from OpenAlex

Ion chromatography with suppressed conductivity detection was used to analyze water samples of swimming pools in Hong Kong which were disinfected by sodium hypochlorite treatment as well as ozone with residual chlorination treatment. The concentrations of the following inorganic anions and disinfection byproducts: fluoride, bromate, hypochlorite, chloride, nitrite, chlorate, nitrate, orthophosphate and sulfate were reported.The levels of fluoride, hypochlorite, nitrite, nitrate and sulfate were within ranges recommended for drinking water. Bromate was found in the ozonated pool, but not in the chlorinated pool. Although regulation of its concentration is not required in swimming pools, it is needed in drinking water treated by ozonation. Its high level in the ozonated pool does pose a concern though bathers only ingest the pool water occasionally.Moreover, the variation of anion concentrations at different climate is discussed. This is the first report on anion analysis on swimming pool water based on an ion chromatographic method developed for drinking water analysis.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.002
GPT teacher head0.178
Teacher spread0.176 · 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 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

Citations0
Published2000
Admission routes1
Has abstractyes

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