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Record W4401344899 · doi:10.1111/ggr.12579

Garnet Reference Materials for <i>In Situ</i> Lu‐Hf Geochronology

2024· article· en· W4401344899 on OpenAlexafffund
Bruno Vieira Ribeiro, Christopher L. Kirkland, Matthijs A. Smit, Kira Musiyachenko, Fawna J. Korhonen, Noreen J. Evans, Kai Rankenburg, Bradley J. McDonald, Stijn Glorie, Sarah Gilbert, Karsten Goemann, I Belousov, Jeffrey Oalmann, Chris Clark, Sean Makin

Bibliographic record

VenueGeostandards and Geoanalytical Research · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of British Columbia
FundersBritish Columbia Knowledge Development FundNatural Sciences and Engineering Research Council of CanadaCurtin University of TechnologyGeological Survey of Western AustraliaAustralian Government
KeywordsGeochronologyIn situGeologyMineralogyGeochemistryRadiochemistryMaterials scienceChemistry

Abstract

fetched live from OpenAlex

In situ garnet Lu‐Hf geochronology has the potential to revolutionise the chronology of petrological and tectonic processes, yet there is a paucity of well‐characterised reference materials to account for laser‐induced matrix‐dependant elemental fractionation. Here, we characterise two reference garnets GWA‐1 (Lu ~ 7.0 μg g−1) and GWA‐2 (Lu ~ 8.5 μg g−1) for in situ garnet Lu‐Hf geochronology. Isochron ages from isotope dilution Lu‐Hf analyses yield crystallisation ages of 1267.0 ± 3.0 Ma with initial 176Hf/177Hfi of 0.281415 ± 0.000012 (GWA‐1), and 934.7 ± 1.4 Ma with 176Hf/177Hfi of 0.281386 ± 0.000013 (GWA‐2). In situ Lu‐Hf analyses yield inverse isochron ages up to 10% older than the known crystallisation age due to matrix effects between garnet and reference glass (NIST SRM 610) under different instrument tuning conditions. This apparent age offset is reproducible for both materials within the same session and can be readily corrected to obtain accurate ages. Our results demonstrate that GWA‐1 and GWA‐2 are robust reference materials that can be used to correct for matrix‐analytical effects and also to assess the accuracy of in situ Lu‐Hf garnet analyses across a range of commonly encountered garnet compositions.

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)0.002
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 score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.007

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 head0.057
GPT teacher head0.345
Teacher spread0.288 · 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

Citations9
Published2024
Admission routes2
Has abstractyes

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