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Record W2117683602 · doi:10.1029/2006gc001283

High‐precision isotopic characterization of USGS reference materials by TIMS and MC‐ICP‐MS

2006· article· en· W2117683602 on OpenAlexafffund
Dominique Weis, Bruno Kieffer, C. Maerschalk, Jane Barling, Jeroen de Jong, Gwen Williams, Diane Hanano, Wilma Pretorius, Nadine Mattielli, James S. Scoates, Arnaud Goolaerts, Richard M. Friedman, J. Brian Mahoney

Bibliographic record

VenueGeochemistry Geophysics Geosystems · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsUniversity of British Columbia
FundersDivision of Ocean SciencesNatural Sciences and Engineering Research Council of CanadaU.S. Geological Survey
KeywordsRadiogenic nuclideGeologyAndesiteRhyoliteIsotope analysisIsotopic signatureIsotopeGeochemistryGeological surveyBasaltHomogeneousMineralogyVolcanic rockGeophysics

Abstract

fetched live from OpenAlex

The Pacific Centre for Isotopic and Geochemical Research (PCIGR) at the University of British Columbia has undertaken a systematic analysis of the isotopic (Sr, Nd, and Pb) compositions and concentrations of a broad compositional range of U.S. Geological Survey (USGS) reference materials, including basalt (BCR‐1, 2; BHVO‐1, 2), andesite (AGV‐1, 2), rhyolite (RGM‐1, 2), syenite (STM‐1, 2), granodiorite (GSP‐2), and granite (G‐2, 3). USGS rock reference materials are geochemically well characterized, but there is neither a systematic methodology nor a database for radiogenic isotopic compositions, even for the widely used BCR‐1. This investigation represents the first comprehensive, systematic analysis of the isotopic composition and concentration of USGS reference materials and provides an important database for the isotopic community. In addition, the range of equipment at the PCIGR, including a Nu Instruments Plasma MC‐ICP‐MS, a Thermo Finnigan Triton TIMS, and a Thermo Finnigan Element2 HR‐ICP‐MS, permits an assessment and comparison of the precision and accuracy of isotopic analyses determined by both the TIMS and MC‐ICP‐MS methods (e.g., Nd isotopic compositions). For each of the reference materials, 5 to 10 complete replicate analyses provide coherent isotopic results, all with external precision below 30 ppm (2 SD) for Sr and Nd isotopic compositions (27 and 24 ppm for TIMS and MC‐ICP‐MS, respectively). Our results also show that the first‐ and second‐generation USGS reference materials have homogeneous Sr and Nd isotopic compositions. Nd isotopic compositions by MC‐ICP‐MS and TIMS agree to within 15 ppm for all reference materials. Interlaboratory MC‐ICP‐MS comparisons show excellent agreement for Pb isotopic compositions; however, the reproducibility is not as good as for Sr and Nd. A careful, sequential leaching experiment of three first‐ and second‐generation reference materials (BCR, BHVO, AGV) indicates that the heterogeneity in Pb isotopic compositions, and concentrations, could be directly related to contamination by the steel (mortar/pestle) used to process the materials. Contamination also accounts for the high concentrations of certain other trace elements (e.g., Li, Mo, Cd, Sn, Sb, W) in various USGS reference materials.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0070.005
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.004
GPT teacher head0.183
Teacher spread0.179 · 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 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

Citations1,083
Published2006
Admission routes2
Has abstractyes

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