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Record W2167619301 · doi:10.1111/gfl.12132

Can argillaceous formations isolate nuclear waste? Insights from isotopic, noble gas, and geochemical profiles

2015· article· en· W2167619301 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGeofluids · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsUniversity of British ColumbiaUniversity of OttawaUniversity of Saskatchewan
Fundersnot available
KeywordsGeologyGroundwaterRadioactive wasteDiffusionOil shaleGeochemistryEarth scienceGeotechnical engineeringChemistryPaleontology

Abstract

fetched live from OpenAlex

Abstract There is considerable interest in the use of thick argillaceous geologic formations to contain nuclear waste. Here, we show that diffusion can be the controlling transport process in these formations and diffusional time scales for δ 18 O and δ 2 H in water, dissolved He, and Cl transport in shale‐dominated aquitards are typically over 10 6 years, well exceeding the regulatory requirements for isolation in most countries. Our scientific understanding of diffusive solute transport processes through argillaceous formations would benefit from the application of additional isotopic tracers (e.g., using new 4 He sampling technology), multidimensional diffusive‐dispersive modeling of groundwater flow and diffusive‐dispersive solute transport over long geologic time scales, and an improved understanding of spatial heterogeneity as well as time‐dependent changes in the subsurface conditions and properties of argillaceous formations in response to events such as glaciation. Based on our current isotopic and geochemical understanding of transport, we argue that argillaceous formations can provide favorable long‐term conditions for isolating nuclear wastes.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.647
Threshold uncertainty score0.486

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 head0.010
GPT teacher head0.191
Teacher spread0.181 · 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