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Record W2090346131 · doi:10.1021/ac025671p

Inductively Coupled Plasma Mass Spectrometry with On-Line Leaching:  A Method To Assess the Mobility and Fractionation of Elements

2002· article· en· W2090346131 on OpenAlexafffund
Diane Beauchemin, Kurt Kyser, Don Chipley

Bibliographic record

VenueAnalytical Chemistry · 2002
Typearticle
Languageen
FieldChemistry
TopicAnalytical chemistry methods development
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaCameco
KeywordsChemistryLeaching (pedology)ReagentAnalyteInductively coupled plasma mass spectrometryInductively coupled plasmaMass spectrometrySample preparationFractionationContaminationAnalytical Chemistry (journal)ChromatographyPlasma

Abstract

fetched live from OpenAlex

A new technique has been developed to assess the mobility and site of specific elements in complex natural materials such as rocks. Concentration profiles during leaching were obtained by pumping reagents (water, 1% HNO3, 10% HNO3, 30% HNO3), either continuously or with flow injection, through a microcolumn of sample while continuously monitoring analyte signals by inductively coupled plasma mass spectrometry (ICPMS). Compared to batch extraction procedures normally used, the approach involves minimal sample preparation and reduced contamination since the leaching is performed in a closed system. Continuous on-line monitoring also allows a greater resolution of the various phases reacting with given reagent. Compared to continuous leaching, flow injection increased the resolution of the various phases using discrete injections of reagents while reducing reagent consumption and minimizing etching of the MS interface. Furthermore, sensitivity was preserved by injecting into air instead of an aqueous carrier. Whether in the continuous or flow injection modes, the proposed approach provides real-time data on what phases are breaking down and what metals are released. It can therefore be used to design effective leaching strategies and to trace isotopic compositions. However, the resulting spectra are complex and the correct determination of some elements requires high-resolution ICPMS.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.159
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.081
GPT teacher head0.349
Teacher spread0.268 · 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

Citations61
Published2002
Admission routes2
Has abstractyes

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