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Record W2560147444 · doi:10.2166/wqrj.2010.036

Potential Aquatic Health Impacts of Selected Dechlorination Chemicals

2010· article· en· W2560147444 on OpenAlexaffabout
Onita D. Basu, Sarah Dorner

Bibliographic record

VenueWater Quality Research Journal · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsPolytechnique MontréalCarleton University
Fundersnot available
KeywordsSodium thiosulfateDaphnia magnaChemistryEffluentThiosulfateSodium bisulfiteEnvironmental chemistryChlorineWastewaterHydrogen peroxideSulfiteSodium metabisulfiteSodium sulfiteEcotoxicitySodiumToxicityEnvironmental engineeringSulfurEnvironmental scienceInorganic chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Municipal wastewater effluents are one of the largest single effluent discharges in Canada. Chlorination of wastewater effluents is a widespread practice throughout Canada (excluding Quebec), the United States and parts of Europe. As chlorine in wastewater effluents is toxic to aquatic biota, dechlorination chemicals may be used to reduce residual chlorine concentrations to below 0.02 mg/L (as Cl2) as mandated by Canadian law. However, the potential aquatic health impacts of residual dechlorination chemicals must also be determined. Seven dechlorination agents (ascorbic acid, hydrogen peroxide, calcium thiosulfate, sodium sulfite, sodium thiosulfate, sodium metabisulfite, sodium bisulfite) were evaluated with regards to their 48 hour acute toxicity. Tests were conducted using Daphnia magna to identify the acute (48 h) toxicity affects of the dechlorination chemicals over a range of concentrations (0-200 mg/L). Sodium sulfite and thiosulfate were found to have the least aquatic mortality effects while hydrogen peroxide and calcium thiosulfate had the most deleterious effects.

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)0.014
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.073
GPT teacher head0.428
Teacher spread0.355 · 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 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

Citations5
Published2010
Admission routes2
Has abstractyes

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