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Complete Trace Elemental Characterisation of Granitoid (USGS G‐2, GSP‐2) Reference Materials by High Resolution Inductively Coupled Plasma‐Mass Spectrometry

2006· article· en· W2120461998 on OpenAlexaff
Wilma Pretorius, Dominique Weis, Gwen Williams, Diane Hanano, Bruno Kieffer, James S. Scoates

Bibliographic record

VenueGeostandards and Geoanalytical Research · 2006
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsUniversity of British Columbia
FundersDivision of Ocean Sciences
KeywordsChemistryInductively coupled plasma mass spectrometryAnalytical Chemistry (journal)Aqua regiaInductively coupled plasmaMass spectrometryTrace elementZirconResolution (logic)Certified reference materialsMineralogyDetection limitEnvironmental chemistryGeologyMetalChromatographyPlasmaGeochemistry

Abstract

fetched live from OpenAlex

The United States Geological Survey granitic and granodioritic reference materials G‐2 and GSP‐2 were decomposed in high‐pressure bombs using both HF‐HNO3 and HF‐HNO3‐HClO4 in order to evaluate the feasibility of characterising the entire suite of geologically relevant trace elements through direct analysis with a high‐resolution inductively coupled plasma‐mass spectrometer (HR‐ICP‐MS). The digested samples were diluted to the appropriate levels and analysed at low, medium and high resolution depending on the required sensitivity and potential interferences for each element. Memory effects during analysis of the high field strength elements (HFSE) were negligible when analysed using an all‐Teflon, uncooled sample introduction system and combined with adequate wash times with 4% v/v aqua regia + 0.5% v/v HF between samples. The concentration of the remaining lithophile elements was determined with a conventional, cooled, Scott‐type spray chamber using a wash solution of 1% v/v HNO3. Total procedural blanks contributed between 0.01 to 0.5% to final sample concentrations and blank subtractions were typically unnecessary. Abundances for Li, Hf, Ba, Zr, Ga, Rb, Sr, La, Ce, Th and U were systematically higher, while those for the heavy rare earth elements (HREEs), Cu and Y were systematically lower in this study compared to USGS values for G‐2 and GSP‐2. This is likely to be related to, respectively, higher recoveries from more efficient digestion of refractory phases (i.e., zircon, tourmaline), and better resolution of interferences when using a HR‐ICP‐MS. Sample digestion experiments also showed that perchloric acid digestion in high pressure bombs resulted in superior recoveries and better precision for the bulk of the trace elements analysed. The concentration of the remaining elements overlapped within uncertainty with recommended reference values and with values determined in other studies using isotope‐dilution TIMS, ICP‐MS and XRF. Concentrations for the elements Cd, Sn, Sb, Ta, Bi, Tb, Ni and Mo are also reported for G‐2 and GSP‐2 reference materials. Our study shows therefore that it is feasible to determine thirty‐nine geologically relevant trace elements accurately and directly in granitoid sample digests when using a HR‐ICP‐MS, thereby negating the need for ion exchange or isotopic spiking.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.039
GPT teacher head0.301
Teacher spread0.262 · 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

Citations104
Published2006
Admission routes1
Has abstractyes

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