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Record W2567709984 · doi:10.5942/jawwa.2017.109.0037

Estimation of NDMA Precursor Loading in Source Water via Artificial Sweetener Monitoring

2016· article· en· W2567709984 on OpenAlexaboutno aff
Matthew Prescott, Stuart W. Krasner, Yingbo Guo

Bibliographic record

VenueAmerican Water Works Association · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Treatment and Disinfection
Canadian institutionsnot available
FundersWater Research FoundationDepartment of Water Resources
KeywordsSucraloseWatershedEnvironmental scienceWastewaterSewage treatmentHydrology (agriculture)Environmental engineeringEnvironmental chemistryChemistryFood science

Abstract

fetched live from OpenAlex

Sucralose is an artificial sweetener and an indicator of wastewater impacts in drinking water. N ‐nitrosodimethyamine (NDMA) is a disinfection by‐product with wastewater‐derived precursors. In two studies conducted in the United States and Canada, data showed watershed and region‐specific relationships between sucralose occurrence, stream flow, and NDMA formation potential (FP). In addition, other water supplies have been identified with high NDMA FP that were low in sucralose, which appeared to be impacted by other sources of precursors in the watershed during high‐flow events (e.g., runoff). In these studies, seasonal and climatic effects were explored where changes in stream flow (e.g., storm events, droughts) and sucralose and NDMA FP have been well correlated in many watersheds. These studies demonstrate the usefulness of measuring sucralose, including the determination of site‐specific correlations with NDMA FP and temporal variability, as well as determining the likely percentage of treated wastewater in the influent of drinking water treatment plants.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.642
Threshold uncertainty score0.580

Codex and Gemma teacher scores by category

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 communication0.0000.000
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 head0.006
GPT teacher head0.213
Teacher spread0.207 · 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

Citations13
Published2016
Admission routes1
Has abstractyes

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