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Record W4368370738 · doi:10.1002/aws2.1340

Treatability of 18 taste and odor compounds in drinking water using oxidation

2023· article· en· W4368370738 on OpenAlex

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.

Bibliographic record

VenueAWWA Water Science · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Treatment and Disinfection
Canadian institutionsAmerican Water (Canada)
Fundersnot available
KeywordsPermanganateChlorineChemistryGeosminOdorHexanalOzoneOxidizing agentEnvironmental chemistryWater treatmentInorganic chemistryOrganic chemistryEnvironmental engineering

Abstract

fetched live from OpenAlex

Abstract The occurrence of taste and odor (T&O) compounds in drinking water can lead to public concern about quality when left unaddressed, therefore suitable treatment is needed. This study evaluated the treatability of 18 T&O compounds using chlorine, permanganate, and ozone in MilliQ and river water. Nine T&O compounds showed complete oxidation (>99% removal) in all water matrices by ozone. Most of the remaining T&O compounds were removed to >50% by ozone. Alkalinity, pH, and natural organic matter (NOM) had a significant impact on the decay of ozone. Chlorine and permanganate were ineffective (removal <30%) for 2‐methylisoborneol (2‐MIB), geosmin, hexanal, pyrazines, and haloanisoles. Although chlorine achieved complete removal for alkyl sulfides and indole, it was only partially effective for aldehydes and ketones. Permanganate was more effective than chlorine in oxidizing unsaturated aldehydes and ketones. Increased NOM and pH reduced oxidation effectiveness for chlorine, but not permanganate.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.209

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 communication0.0000.001
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 head0.028
GPT teacher head0.259
Teacher spread0.231 · 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