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Record W2007216521 · doi:10.1021/ac026466c

Comparison of High-Field Asymmetric Waveform Ion Mobility Spectrometry with GC Methods in Analysis of Haloacetic Acids in Drinking Water

2003· article· en· W2007216521 on OpenAlexaff
Wojciech Gabryelski, Fengwu Wu, Kenneth L. Froese

Bibliographic record

VenueAnalytical Chemistry · 2003
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsUniversity of Alberta
FundersAmerican Water Works Association Research Foundation
KeywordsHaloacetic acidsChemistryIon-mobility spectrometryChromatographyAnalyteMass spectrometryElectrospray ionizationMatrix (chemical analysis)ElectrosprayDetection limitOrganic chemistryChlorine

Abstract

fetched live from OpenAlex

Haloacetic acids (HAAs) are major byproducts of chlorination of drinking water. Electrospray ionization high-field asymmetric waveform ion mobility spectrometry mass spectrometry (ESI-FAIMS-MS) provides a tool for direct monitoring of these compounds. However, treated drinking water samples can be challenging to analyze due to the large number of chemicals present and due to matrix effects that can hinder quantitation of analytes. We developed a standard addition ESI-FAIMS-MS method that permits submicrogram per liter detection of haloacetic acids and overcomes matrix effects. An advantage of FAIMS is increased selectivity through a significant reduction in the chemical background from ESI. Moreover, detection limits with this method are much lower than with previously existing GC and GC/MS methods, and quantitation results compare favorably with other existing methods. This new method does not require sample preparation or chromatographic separation and provides a fast, simple, sensitive, and selective method for monitoring HAAs.

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 categoriesInsufficient payload (model declined to judge)
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 score0.614
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.342
Teacher spread0.323 · 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.

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

Citations51
Published2003
Admission routes1
Has abstractyes

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