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Dating Micrometre‐Thin Rims Using a <scp>LA</scp>‐<scp>ICP</scp>‐<scp>MS</scp> Depth Profiling Technique on Zircon from an Archaean Metasediment: Comparison with the <scp>SIMS</scp> Depth Profiling Method

2014· article· en· W2113229288 on OpenAlexaff
C J Kelly, Christopher R.M. McFarlane, David Schneider, Simon E. Jackson

Bibliographic record

VenueGeostandards and Geoanalytical Research · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsGeological Survey of CanadaNatural Resources CanadaUniversity of New BrunswickUniversity of Ottawa
Fundersnot available
KeywordsZirconMineralogyAnalytical Chemistry (journal)GeologyChemistryGeochemistryChromatography

Abstract

fetched live from OpenAlex

Laser ablation‐inductively coupled plasma‐mass spectrometry ( LA ‐ ICP ‐ MS ) was examined as a tool for measuring isotopic variation as a function of ablation depth in unpolished zircon from an Archaean metasediment specimen. This technique was able to identify micrometre‐thin (&gt; 3 μm) isotopically distinct mineral domains characterised by ca . 100 Myr younger 207 Pb/ 206 Pb ages associated with 2 s age uncertainties as low ~ 0.2%, as well as elevated U content relative to grain interiors (up to an order of magnitude). Our calculated drilling rate suggests that each laser pulse excavated depths of ~ 0.06 μm. Ages resolved through the LA ‐ ICP ‐ MS methods overlap the 2 s uncertainties of 207 Pb/ 206 Pb ages measured using SIMS depth profiling on the same zircon population. The rims were further evinced by the detection of relative enrichment (&gt; 3 orders of magnitude) in REE in the outermost micrometres of the same zircon, measured using a different and independent LA ‐ ICP ‐ MS depth profiling technique. We propose a LA ‐ ICP ‐ MS U–Pb technique capable of quickly identifying and quantifying rims, which are indication of late, yet geologically significant, fluid events that are otherwise undefined.

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)0.016
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.767
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.003
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.004
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 head0.055
GPT teacher head0.350
Teacher spread0.295 · 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.

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

Citations31
Published2014
Admission routes1
Has abstractyes

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