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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 OpenAlex
Walt Bayless, Robert C. Andrews

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.108

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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