MétaCan
Menu
Back to cohort
Record W4408443636 · doi:10.5194/egusphere-egu25-3355

Glaciation-induced radionuclide mobility from the Kiggavik uranium deposits: natural analogues for geological disposal of nuclear waste

2025· preprint· en· W4408443636 on OpenAlexaffabout
Ian Burron, Mostafa Fayek, Julie Brown

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicRadioactive contamination and transfer
Canadian institutionsCanadian Nuclear Safety CommissionUniversity of WinnipegUniversity of Manitoba
Fundersnot available
KeywordsRadionuclideUraniumRadioactive wasteNatural (archaeology)GeologyGlacial periodUranium oreGeochemistryEnvironmental scienceRadiochemistryWaste managementMining engineeringChemistryMaterials scienceEngineeringMetallurgyGeomorphologyPaleontologyNuclear physics

Abstract

fetched live from OpenAlex

Safe and effective disposal of Used Nuclear Fuel (UNF) within a Deep Geological Repository (DGR) must isolate and contain UNF from the biosphere for ~1 Ma. This time period is long enough for several glacial cycles to elapse; it is therefore important to understand how glaciation-related processes such as erosion and subsurface fluid infiltration may impact a DGR. Studying the history of uranium (U) minerals from U deposits, which have been impacted by Pleistocene glaciation, provides a natural analogue to investigate the potential impacts of glaciation on a DGR over Ka-Ma timescales.               Uranium deposits in the Kiggavik region, Nunavut, Canada occur from surface to a depth of ~500m (comparable to depths of proposed DGRs) and have been impacted by multiple post-depositional fluid events and glacial cycles. Uranium minerals comprising uraninite, coffinite, brannerite, and U-Th-Zr silicates are hosted by illite (clay) and hematite altered metasedimentary and granitic rocks. Most U minerals (U1+U2) yield ~1.55-0.3 Ga U-Pb ages indicating they have remained in-situ since before the emergence of dinosaurs despite experiencing multiple fluid infiltration events.A smaller subset of U minerals (U3) shows stronger evidence of remobilization. U3 minerals are concentrated along redox fronts developed between geothite-bearing oxidized and bleached (clay-dominated) host rocks. These redox boundaries occur within ~5 cm of U1/U2 minerals, and are strongly associated with open fractures and porous veins. U3 minerals have 235U/207Pb ages of >0.6-65 Ma, providing minimum ages of complete recrystallization and potential large-scale radionuclide release.Uranium-thorium disequilibrium geochronology indicates widespread leaching of soluble decay-chain isotopes, corresponding to smaller-scale release of radionuclides. This has occurred sporadically between 34-494 Ka, with major episodes correlating with periods of rapid climate change during glaciation. Oxygen and hydrogen stable isotopic values of Illite associated with U3 indicate isotopic exchange with high-latitude meteoric fluids (i.e. snow/glacial melt).                 The history of U mobility in the Kiggavik region indicates oxidized glacial-derived fluids may infiltrate ≥500m into the subsurface along open fractures and mobilize radionuclides. This mobility occurs cumulatively over multiple glacial cycles and corresponds with ages of climate-induced perturbations to overlying ice sheets. Although longer distance transport from the system cannot be ruled out, the proximity of U3 to U1/U2 mineralization suggests overall transport distances are short (several cm), and geochronology indicates transport timescales are long (10’s-100’s Ka). Interactions with minerals present in both metasedimentary and granitic host rocks such as illite clay, U-oxides, and Ti-oxides have effectively restricted radionuclide mobility to rates millions of times slower than glacial movement over timescales comparable to human evolution.

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 score0.251
Threshold uncertainty score0.701

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 science0.0010.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.245
Teacher spread0.231 · 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 routes2
Has abstractyes

Explore more

Same topicRadioactive contamination and transferFrench-language works237,207