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Record W1961420818 · doi:10.1002/rcm.7407

Stable chlorine isotope analysis of chlorinated acetic acids using gas chromatography/quadrupole mass spectrometry

2015· article· en· W1961420818 on OpenAlexaff
Milena E. Miska, Orfan Shouakar‐Stash, Henry Holmstrand

Bibliographic record

VenueRapid Communications in Mass Spectrometry · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsUniversity of Waterloo
FundersEuropean Commission
KeywordsChemistryMass spectrometryGas chromatographyChlorineChromatographyIsotopes of chlorineGas chromatography–mass spectrometryIsotope-ratio mass spectrometryIsotopeThermal ionization mass spectrometryIsotope dilutionStable isotope ratioAcetic acidAnalytical Chemistry (journal)Isotope analysisIonizationOrganic chemistryIon

Abstract

fetched live from OpenAlex

RATIONALE: The environmental occurrence of chlorinated acetic acids (CAAs) has been extensively studied, but the sources and transport are still not yet fully understood. A promising approach for source apportionment and process studies is the isotopic characterization of target compounds. We present the first on-line stable chlorine isotope analysis of CAAs by use of gas chromatography/quadrupole mass spectrometry (GC/qMS). METHODS: Following approved procedures for concentration analysis, CAAs extracted into MTBE were methylated to GC-amenable methyl esters (mCAAs). These mCAAs were then analyzed by GC/qMS for their stable chlorine isotope composition using a sample/standard-bracketing approach (CAA standards in the range δ(37) Cl -6.3 to -0.2 ‰, Standard Mean Ocean Chloride). RESULTS: Cross-calibration of the herein presented method with off-line reference methods (thermal ionization and continuous-flow GC isotope ratio mass spectrometry; TI-MS and CF-GC/IRMS, respectively) shows good agreement between the methods (regression slope for GC/qMS vs reference method data sets: 0.92 ± 0.29). Sample amounts as small as 10 pmol Cl can herewith be analyzed with a precision of 0.1 to 0.4 ‰. CONCLUSIONS: This method should be useful for environmental studies of CAAs at ambient concentrations in precipitations (<0.06 to 100 nmol L(-1) ), surface waters (<0.2 to 5 nmol L(-1) ) and soil (<0.6 to 2000 nmol kg(-1) dry soil) where conventional off-line methods cannot be applied.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.038
GPT teacher head0.266
Teacher spread0.228 · 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 designObservational
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

Citations6
Published2015
Admission routes1
Has abstractyes

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