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Record W127319847 · doi:10.2166/wqrj.2006.041

Assessing the Disinfecting Power of Chlorite in Drinking Water

2006· article· en· W127319847 on OpenAlexaff
Françoise Bichai, Benoît Barbeau

Bibliographic record

VenueWater Quality Research Journal · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Treatment and Disinfection
Canadian institutionsPolytechnique MontréalNatural Sciences and Engineering Research Council of Canada
Fundersnot available
KeywordsDisinfectantChloriteBacillus subtilisSporeChemistryMicroorganismSodium chloriteHeterotrophMicrobiologyBacteriaEnvironmental chemistryFood scienceBiologyChlorine dioxideInorganic chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The goal of this study was to review and confirm experimentally chlorite effectiveness as a drinking water disinfectant. The steps in the experiment were a series of laboratory assays performed on three types of microorganisms, Bacillus subtilis spores, MS2 coliphages, as well as heterotrophic (HPC) bacteria, to verify chlorite action in water. The tests showed that chlorites have no disinfectant effect on B. subtilis spores (CT > 106 mg min/L), that they slightly decrease HPC bacterial regrowth and, finally, that a dose of 1 and 10 mg ClO2-/L can inactivate almost 2 log and 4.5 log of MS2 phages, respectively, after 9 days of contact time. It would therefore appear that chlorites are not a good primary disinfectant, but do exhibit a bacteriostatic effect.

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)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.086
GPT teacher head0.405
Teacher spread0.319 · 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.

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

Citations6
Published2006
Admission routes1
Has abstractyes

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