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Record W2007716359 · doi:10.2166/wh.2007.002

Biodegradation of six haloacetic acids in drinking water

2007· article· en· W2007716359 on OpenAlexafffund
Walt Bayless, Robert C. Andrews

Bibliographic record

VenueJournal of Water and Health · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Treatment and Disinfection
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHaloacetic acidsTrichloroacetic acidChemistryChlorineBiodegradationBiofilmAcetic acidEnvironmental chemistryMicroorganismWater treatmentChromatographyBacteriaOrganic chemistryEnvironmental engineeringBiologyEnvironmental science

Abstract

fetched live from OpenAlex

Haloacetic acids (HAAs) are produced by the reaction of chlorine with natural organic matter and are regulated disinfection by-products of health concern. Biofilms in drinking water distribution systems and in filter beds have been associated with the removal of some HAAs, however the removal of all six routinely monitored species (HAA(6)) has not been previously reported. In this study, bench-scale glass bead columns were used to investigate the ability of a drinking water biofilm to degrade HAA(6). Monochloroacetic acid (MCAA) and monobromoacetic acid (MBAA) were the most readily degraded of the halogenated acetic acids. Trichloroacetic acid (TCAA) was not removed biologically when examined at a 90% confidence level. In general, di-halogenated species were removed to a lesser extent than the mono-halogenated compounds. The order of biodegradability by the biofilm was found to be monobromo > monochloro > bromochloro > dichloro > dibromo > trichloroacetic acid.

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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.019
GPT teacher head0.272
Teacher spread0.253 · 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

Citations65
Published2007
Admission routes2
Has abstractyes

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