MétaCan
Menu
Back to cohort

Accurate Determination of Silver Isotopic Composition in Silicate Rocks with Low Silver Abundance

2023· article· en· W4387501036 on OpenAlexaff
Yuan-Feng Zhu, Hai–Zhen Wei, Junlin Wang, Anthony E. Williams‐Jones, Zaicong Wang, Shao‐Yong Jiang, Simon V. Hohl, Chun Huan, Miaomiao Zhang

Bibliographic record

VenueACS Earth and Space Chemistry · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeochemistry and Elemental Analysis
Canadian institutionsMcGill University
FundersNanjing UniversityNational Natural Science Foundation of China
KeywordsSilicateIsobaric processAnalytical Chemistry (journal)Mantle (geology)Matrix (chemical analysis)Silicate mineralsMineralogyDopingIsotopeBasaltNatural abundanceMaterials scienceChemistryGeologyMass spectrometryGeochemistryEnvironmental chemistryPhysicsThermodynamics

Abstract

fetched live from OpenAlex

Owing to the extremely low abundance of silver in the Earth’s crust and mantle, it remains a major challenge to eliminate matrix impurities to obtain accurate silver isotopic compositions in silicate rocks. To determine precise and accurate silver isotopic data in silicates, we have modified the traditional pretreatment procedures, assessed isobaric interference and matrix effects, and analyzed silver isotopic compositions in silicates. By modification of the silicate digestion and ion-exchange procedures, efficient elution of silver was achieved. The doping experimental results indicated that the matrix effect induced by Ti and Cr could be satisfactorily corrected using the internal standard Pd isotope pair of 108 Pd– 106 Pd. The modified chemical chromatographic method effectively separates Ni from Ag in silicate samples, thereby minimizing the significant isobaric interference from Ni cations. As a result, the shifts in the δ 109 Ag value caused by cations can be corrected to less than 0.02‰. There are considerable shifts down to −0.82‰ in δ 109 Ag from the accepted δ 109 Ag value when soluble metasilicate is present in the solution, which might explain the discrepancies in measured δ 109 Ag values for silicate materials. To accurately analyze silver isotopic compositions, especially of silicates with extremely low silver abundance, a silver standard doping method with an optimum doping proportion (sample-to-standard material ratio of 2:8) has been shown to produce an acceptable measurement uncertainty from 0.04 to 0.06‰ (2SD). The high-precision δ 109 Ag value determined in this study for ultramafic rocks from Balmuccia and the basalt reference material, BHVO-2, of −0.044 ± 0.062‰ is consistent with that of −0.16 ± 0.07‰ reported by previous studies. Our study paves the way for the more extensive use of silver isotopes in studies of terrestrial/extraterrestrial rocks, something that will be of help in constraining the sources of precious metals in polymetallic ore deposits as well as core formation and volatile-element depletion in the early solar system.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.433
Threshold uncertainty score0.376

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.006
GPT teacher head0.197
Teacher spread0.191 · 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 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

Citations2
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueACS Earth and Space ChemistrySame topicGeochemistry and Elemental AnalysisFrench-language works237,207