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Record W2026305667 · doi:10.2166/ws.2009.506

Variations of DBPs precursors according to location within the distribution system

2009· article· en· W2026305667 on OpenAlexaff
Christine Beaulieu, Manuel J. Rodríguez, Jean Sérodes

Bibliographic record

VenueWater Science & Technology Water Supply · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Treatment and Disinfection
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHaloacetic acidsFractionationReactivity (psychology)ChemistryEnvironmental chemistryFraction (chemistry)Organic matterChromatographyOrganic chemistryChlorine

Abstract

fetched live from OpenAlex

Little information is available on the evolution of remaining organic matter (ROM) in a water distribution system (WDS) and its impact on the generation of disinfection by-products (DBPs). This research involves the characterization, through sample fractionation processes and experimental chlorination tests, of the reactivity of DBP precursors occurring within a WDS. The study is based on samples collected in various locations of a WDS during a complete year. For each sample, six fractions were generated to determine their potential for formation of trihalomethanes (THMs) and haloacetic acids (HAAs). Fractionation processes on ROM demonstrated that the spatial behavior of precursors for THMs differs from that for precursors of HAAs. In addition, experimental chlorination tests showed that the reactivity of the investigated fractions, in terms of DBP formation potential (DBPfp), was different from each other according to location in the WDS. DBPfp for the studied fractions changed drastically during water treatment. However, changes of DBPfp for fractions were relatively low between the beginning and the extremity of the distribution system. Since the results of this research confirm that the ability to produce DBPs is related to the nature of the fractions, they could be useful to evaluate the impact of re-chlorination on DBP formation in a WDS.

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 score0.212
Threshold uncertainty score0.607

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.004
GPT teacher head0.203
Teacher spread0.198 · 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

Citations1
Published2009
Admission routes1
Has abstractyes

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