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Record W4406882414 · doi:10.5194/egusphere-2025-55

Rapid dose rate estimation for trapped charge dating using pXRF measurements of potassium concentration

2025· preprint· en· W4406882414 on OpenAlexafffund
Sam Woor, Mitch D’Arcy, Olav B. Lian, Maria Schaarschmidt, Julie A. Durcan

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPhysics and Astronomy
TopicX-ray Spectroscopy and Fluorescence Analysis
Canadian institutionsUniversity of the Fraser ValleyUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPotassiumEstimationEnvironmental scienceChemistryStatisticsMaterials scienceMathematicsEconomicsMetallurgy

Abstract

fetched live from OpenAlex

Abstract. Quantifying environmental radiation dose rates is an essential step in age calculation using trapped charge dating methods. A means of rapid dose rate estimation would therefore be useful for a variety of reasons, especially in contexts where rapid equivalent dose estimates are available. For instance, for informing sampling strategy, providing initial age estimates, or supporting portable luminescence studies. However, high-precision methods often used for calculating dose rates are typically time consuming and expensive and are impractical for such ‘range-finder’ applications. Portable X-ray fluorescence (pXRF) offers a rapid means of measuring the Potassium (K) concentration of sediment, although the other radionuclides typically used to calculate dose rates (Uranium (U) and Thorium (Th)) fall beneath its detection limits at the quantities at which they are usually present in sediments. In this study, we investigate whether pXRF measurements of K concentration alone can be used to accurately estimate total environmental dose rates. A large, global training dataset of 1473 radionuclide samples is used to generate a set of linear relationships between (1) K concentration and external beta dose rate; (2) external beta and gamma dose rates; and (3) external gamma and alpha dose rates. We test the utility of these relationships by measuring the K contents of 67 sediment samples with independent high-precision radionuclide data from a variety of contexts using pXRF. The resulting K concentrations are then converted to external dose rate estimates using the training equations. A simplified set of attenuation parameters are used to correct infinite matrix dose rate estimates, and these are combined with cosmic ray and internal contributions to rapidly calculate total environmental dose rates for a range of theoretical, common luminescence dating scenarios (such as 180–250 μm quartz that has undergone etching). Results show that pXRF can accurately measure K concentrations in a laboratory setting. The training equations can predict external beta dose rates accurately based on K content alone, whilst external alpha dose rates are predicted less accurately. In combination, total estimated dose rates show good agreement with their counterparts calculated from high-precision methods, with 68–98 % of our results lying within ±20 % of unity depending on the scenario. We report better agreement for scenarios where alpha contributions are assumed to be negligible (e.g., in the case of etched, coarse-grained quartz or potassium feldspar). The use of simplified attenuation factors to correct estimated infinite matrix dose rates does not contribute significantly to resulting scatter, with uncertainties mostly resulting from the training equations. This study serves as a proof of concept that pXRF measurements, along with a set of linear equations and a simplified correction procedure, can be used to rapidly calculate range-finder environmental dose rates.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.886
Threshold uncertainty score0.931

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.058
GPT teacher head0.328
Teacher spread0.271 · 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.

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

Citations1
Published2025
Admission routes2
Has abstractyes

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