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Record W3145328124 · doi:10.1029/2020jb020998

Analysis of Crystalline Rock Permeability Versus Depth in a Canadian Precambrian Rock Setting

2021· article· en· W3145328124 on OpenAlexafffundabout
A. P. Snowdon, Stefano D. Normani, J. F. Sykes

Bibliographic record

VenueJournal of Geophysical Research Solid Earth · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsUniversity of Waterloo
FundersNuclear Waste Management Organization
KeywordsPrecambrianGeologyLithologyPlutonPermeability (electromagnetism)GeochemistryShieldPetrologySeismologyChemistry

Abstract

fetched live from OpenAlex

Abstract Over the last 50 years, there has been an increased interest in characterizing Precambrian crystalline rock, such as the Canadian Shield, to investigate the feasibility of deep geologic repositories for isolating used nuclear fuel from the biosphere. Extensive work has been conducted in Canada with a large amount of that work undertaken by Atomic Energy of Canada Limited. Few peer‐reviewed journal articles were published based on these data, so a large amount of the data, specifically on fracture zones, are unavailable for modelers and analysts. By collecting and analyzing over one‐hundred technical reports, journal articles, and conference proceedings, written between 1975 and 1996, it was possible to characterize plutonic Precambrian crystalline rock and separate the data into (1) equivalent porous media (EPM) for rock mass and (2) fracture zones (FZs). A third category, aggregate media (AM), was used herein to represent the entire data set (EPM + FZs). Using the data from these studies, a novel logistic function was fit to represent the mean permeability, with respect to depth, of crystalline rock for EPMs and FZs in plutons. Understanding rock permeability is critical for the long‐term isolation of used nuclear fuel so that accurate predictions of fluid flow and mass transport can be evaluated in the area of the proposed storage location.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.511
Threshold uncertainty score0.943

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.034
GPT teacher head0.332
Teacher spread0.298 · 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

Citations29
Published2021
Admission routes3
Has abstractyes

Explore more

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