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Record W4388160105 · doi:10.3390/min13111381

Effects of Paleoregolith and Fault Offset on the Formation of Unconformity-Type Uranium Deposits

2023· article· en· W4388160105 on OpenAlexafffund
Hui Qiu, Hua Lin, Jianwen Yang

Bibliographic record

VenueMinerals · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsUniversity of Windsor
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsUnconformityGeologyRegolithSedimentary rockUranium oreGeochemistryUraniumFault (geology)Structural basinSedimentary basinPetrologyMineralogyGeomorphologySeismology

Abstract

fetched live from OpenAlex

Regional paleoregolith is found to exist immediately below unconformities separating basin fills from basement rocks in sedimentary basins. However, the controlling role of paleoregolith on unconformity-type uranium mineralization has not been quantitatively addressed before. Coupled hydrothermal fluid flow and reactive mass transport modeling are therefore performed in this study by using the software TOUGHREACT. The modeling results reveal that preferential flow occurs in the regolith due to its relatively high permeability in comparison with that of the host rocks. The thicker the regolith is, the more concentrated the fluids in the footwall of a fault zone are, leading to more compact and higher-grade deposits therein, and vice versa. Also, displacement of the regolith caused by fault offset plays an important role, as it appears to control the shape of uranium deposits. When the displacement is less than 30 m, the deposits are characterized by a more compact shape. When the displacement is over 60 m, the deposits extend more laterally and even exhibit a ‘discrete’ shape due to the expelling effect of downslope flow that occurs at the fault offset site.

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 score0.263
Threshold uncertainty score0.135

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 integrity0.0000.000
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 head0.017
GPT teacher head0.216
Teacher spread0.200 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

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