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Dating Old Groundwater with <sup>36</sup>Cl and <sup>81</sup>Kr in a Fractured Claystone Formation, Mecsek Mts., Hungary

2025· article· en· W4410382467 on OpenAlexaff
Marianna Túri, Péter Molnár, Amadé Halász, Mihály Veres, Róbert Janovics, László Palcsu

Bibliographic record

VenueACS Earth and Space Chemistry · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsOptech (Canada)
Fundersnot available
KeywordsGroundwaterGeologyGeochemistryRadiochemistryChemistryGeotechnical engineering

Abstract

fetched live from OpenAlex

The age distribution of groundwater retrieved in two boreholes of a claystone formation in the Mecsek Mountains, Hungary, was investigated using age tracers 81 Kr and 36 Cl, with additional analyses of 4 He, 14 C, and tritium. The present work aims to search a potential site for a high-level radioactive waste repository. Tracer age results provide significant insights into the temporal evolution of the vertical recharge. Radiogenic 4 He concentration increases with depth, and 3 He/ 4 He ratios decreasing toward crustal support the hypothesis of an increasing age with depth. Shallow borehole samples reveal a broad age range, including one with an 81 Kr model age of approximately 34,000 years, and a 14 C model age of 13,400 years. In deeper sections, a 81 Kr model age of 625,000 years was broadly consistent with a 36 Cl model age of ∼400,000 years, indicating the presence of ancient groundwater. Unexpectedly high 81 Kr abundances measured in one borehole indicate underground 81 Kr production in a uranium-rich rock formation, adding to uncertainty of 81 Kr model ages, whereas the obtained 36 Cl ages (∼90,000 to ∼400,000 years) are here considered more reasonable. Noble gas temperatures indicate that recharge occurred during glacial and interglacial periods. This study demonstrates the value of integrating multiple isotopic tracers to address uncertainties in groundwater dating and to provide a robust framework for understanding deep aquifer systems.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.798

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
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 head0.007
GPT teacher head0.214
Teacher spread0.207 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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