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Comment on egusphere-2025-806

2025· peer-review· en· W4409508495 on OpenAlexfundno aff

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
FundersArmy Research OfficeDanmarks Tekniske UniversitetDeutsche ForschungsgemeinschaftHORIZON EUROPE Framework ProgrammeUniversität zu KölnUniversité de LausanneEuropean CommissionUniversity of Regina
KeywordsPsychology

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 %, 12.5 ± 0.5 % or 13 ± 1 % (Huntley and Baril, 1997; Smedley et al., 2012; 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 ~410 nm. However, these assumptions may not apply to all samples and assuming too high K-concentrations 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 ten 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 beta 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; 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 to routinely measure the bulk K-concentration of each sample, complemented by additional single-grain 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)0.002
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.323
Threshold uncertainty score0.966

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0200.010
Insufficient payload (model declined to judge)0.3230.240

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 head0.065
GPT teacher head0.401
Teacher spread0.336 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2025
Admission routes1
Has abstractyes

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