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Record W2507125049 · doi:10.1111/ggr.12146

A Practical Approach for Collecting Large‐<i>n</i> Detrital Zircon U‐Pb Data sets by Quadrupole <scp>LA</scp>‐<scp>ICP</scp>‐<scp>MS</scp>

2016· article· en· W2507125049 on OpenAlexafffund
W. A. Matthews, Bernard Guest

Bibliographic record

VenueGeostandards and Geoanalytical Research · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of Calgary
FundersCanada Foundation for Innovation
KeywordsZirconMineralogyRepeatabilityAnalytical Chemistry (journal)GeologyChemistryChromatographyGeochemistry

Abstract

fetched live from OpenAlex

A measurement procedure for the rapid acquisition of U‐Pb dates for detrital zircons by quadrupole LA ‐ ICP ‐ MS was developed. The procedure achieves a threefold increase in measurement efficiency compared with the most commonly used methods. Utilising reduced background counting times and a shortened ablation period, a throughput of ~ 130 measurements/h can be achieved. The measurement procedure was characterised and validated using data from thirty‐nine sessions acquired over a twelve‐month period. Systematic measurement error in 206 Pb/ 238 U dates for reference materials used for quality control with ages between 28.2 and 2672 Ma was &lt; 1.5%. Average measurement uncertainty, including both random and systematic components, was 1–4% (2 s ). Interrogation of time‐resolved calculated dates and signal intensities for each measurement allows for the detection and elimination of portions of measurements exhibiting age heterogeneities, zoning, lead loss and contamination by common lead. The measurement procedure diminishes the need to acquire cathodoluminescence imagery for routine detrital zircon applications further increasing throughput and reducing cost. The utility of the measurement procedure is demonstrated by the measurement of samples previously characterised by LA ‐ MC ‐ ICP ‐ MS .

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)0.010
metaresearch head score (Gemma)0.060
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.331
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.060
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.084
GPT teacher head0.357
Teacher spread0.274 · 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 designNot applicable
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

Citations73
Published2016
Admission routes2
Has abstractyes

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