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Effective Correction of Mass Bias for Rhenium Measurements by MC‐ICP‐MS

2009· article· en· W2060897833 on OpenAlexafffund
André Poirier, Régis Doucelance

Bibliographic record

VenueGeostandards and Geoanalytical Research · 2009
Typearticle
Languageen
FieldChemistry
TopicRadioactive element chemistry and processing
Canadian institutionsMcGill UniversityUniversité du Québec à Montréal
FundersFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsRheniumFractionationTungstenIsotopeChemistryAnalytical Chemistry (journal)Mass spectrometryMatrix (chemical analysis)Equilibrium fractionationConsistency (knowledge bases)Isotope fractionationSample preparationInductively coupled plasma mass spectrometryRadiochemistryChromatographyInorganic chemistryMathematics

Abstract

fetched live from OpenAlex

The geochemistry of Re‐Os and the recent use of Re as a non‐traditional stable isotope both need accurate and precise quantification of 187 Re/ 185 Re ratios. This paper reports rhenium isotopic data obtained from the analysis of a standard solution and geological samples by MC‐ICP‐MS. We show that measured isotopic ratios are modified by matrix effects that cannot be accounted for by the standard solution bracketing technique. The bias resulting from measurements on a spiked ( 185 Re‐enriched) sample is shown to alter the apparent Re concentration by several percent. When spiking samples and calibrators with tungsten, simultaneous measurement of tungsten and rhenium isotopes compensates for the matrix‐induced modification of mass bias. Rhenium and tungsten are shown to have different fractionation factors. This may be due to the fact that the two elements fractionate in a different but systematic way, or that the reference isotopic ratios used for elemental Re and W are incoherent with one another. The consistency of fractionation through time can be used to obtain an empirical relationship between W and Re measured ratios from a standard solution to obtain a sample's fractionation‐corrected 187 Re/ 185 Re spiked ratio on samples containing pg g −1 levels of Re, even if some matrix capable of affecting mass bias remains in the final solution.

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)0.002
metaresearch head score (Gemma)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.331
Threshold uncertainty score0.632

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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 head0.080
GPT teacher head0.396
Teacher spread0.316 · 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

Citations16
Published2009
Admission routes2
Has abstractyes

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