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Record W1980253900 · doi:10.1039/b508916f

Determination of hexafluoroarsenate in industrial process waters by anion-exchange chromatography-inductively coupled plasma-mass spectrometry (AEC-ICP-MS)

2005· article· en· W1980253900 on OpenAlexaff
Dirk Wallschläger, Jacqueline London

Bibliographic record

VenueJournal of Analytical Atomic Spectrometry · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicArsenic contamination and mitigation
Canadian institutionsTrent University
Fundersnot available
KeywordsChemistryInductively coupled plasma mass spectrometryArsenicIon chromatographyMass spectrometryIon exchangeFluorideDetection limitInductively coupled plasmaHydroxideBiocideEnvironmental chemistryChromatographyInorganic chemistryIonPlasma

Abstract

fetched live from OpenAlex

We describe the first specific method for the determination of the hexafluoroarsenate ion in waters, involving anion-exchange chromatography coupled to inductively coupled plasma-mass spectrometry. The detection limit was estimated to be 6 ng L−1 (as arsenic), and complete separation from all other known inorganic arsenic species and methylated arsenic biocides is accomplished. Hexafluoroarsenate was detected in process water samples from an industrial fluoride-rich environment, where it constituted the vast majority (78–100%) of the total arsenic present. It was not removed from these process waters by iron hydroxide co-precipitation. The analytical and environmental implications of our findings are discussed.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.246
Teacher spread0.234 · 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

Citations7
Published2005
Admission routes1
Has abstractyes

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