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Record W4415363433 · doi:10.5194/gchron-7-475-2025

How much K is OK? Evaluating different methods for K-concentration determination and the effect of the internal K concentration on feldspar luminescence dating

2025· article· en· W4415363433 on OpenAlexfundno aff
Linda Maßon, Svenja Riedesel, Stephan Opitz, Anja Zander, A.M.T. Bell, Hanna Cieszynski, Tony Reimann

Bibliographic record

VenueGeochronology · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsnot available
FundersArmy Research OfficeDanmarks Tekniske UniversitetDeutsche ForschungsgemeinschaftHORIZON EUROPE Framework ProgrammeUniversität zu KölnUniversité de LausanneEuropean CommissionUniversity of Regina
KeywordsLuminescenceAnalytical Chemistry (journal)SpectrometerFeldsparFluorescenceSpectroscopyPotassium

Abstract

fetched live from OpenAlex

Abstract. For luminescence dating of potassium-rich (K) feldspars, the presence of 40K within the K-feldspar grains contributes significantly to the internal dose rate of the sample. Whilst it is common practice to determine uranium, thorium,, and potassium concentrations for external dose rate calculations, the vast majority of studies do not measure the internal K concentration. Instead, most studies apply published K concentrations of 10 ± 2 % (Smedley et al., 2012), 12.5 ± 0.5 % (Huntley and Baril, 1997), or 13 ± 1 % (Zhao and Li, 2005) to their samples. The use of these high literature-based K concentrations is usually justified by two assumptions: (i) only K-feldspar grains with high K concentrations contribute to the luminescence signal significantly, and (ii) we reliably exclude Na-feldspar luminescence signals using filters, with a narrow transmission window around the K-feldspar emission peak of ∼ 410 nm. However, these assumptions may not apply to all samples, and assuming K concentrations that are too high might result in significant dose rate overestimation. To investigate the effect of the internal K concentration on the dose rate and the validity of the above-mentioned assumptions, we determine the K concentration of a set of 10 density-separated sand-sized K-feldspar samples of different geological origin and chemical composition using four different techniques. We quantify their K concentration on the bulk level using a wavelength-dispersive X-ray fluorescence spectrometer and a β counter and on the single-grain level using a micro X-ray fluorescence spectrometer and a scanning electron microscope (SEM) with an energy-dispersive spectroscopy (EDX) attachment. We use the SEM-EDX single-grain results to calculate two luminescence-weighted K estimates. These two estimates, effective K and luminescent grains, connect the K concentration of a grain to its luminescence signal intensity. Our experimental results show that (1) there is a good agreement between bulk and average single-grain K-concentration measurements, (2) single-grain K concentrations within one sample can be highly variable across the entire physically possible range of K concentrations for feldspars, and (3) the blue luminescence emission is not dominated by K-rich feldspar grains. For most samples there are considerable differences between the published and the measured K concentrations. These differences result in overestimation of the total dose rate of up to 34.6 % compared to dose rates calculated using measured K concentrations. We therefore suggest routinely measuring the bulk K concentration of each sample, complemented by additional single-grain K-concentration measurements.

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)0.014
metaresearch head score (Gemma)0.043
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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.043
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
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 head0.021
GPT teacher head0.349
Teacher spread0.328 · 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
GenreMethods

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

Citations3
Published2025
Admission routes1
Has abstractyes

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