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Record W4312070724 · doi:10.31223/x5zp9d

The Low Permeability of the Earth’s Precambrian Crust

2022· preprint· en· W4312070724 on OpenAlexafffund
Grant Ferguson, Jennifer C. McIntosh, Oliver Warr, Barbara Sherwood Lollar

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsUniversity of TorontoUniversity of OttawaGlobal Institute for Water SecurityUniversity of Saskatchewan
FundersNuclear Waste Management OrganizationNatural Sciences and Engineering Research Council of CanadaCanadian Institute for Advanced ResearchGlobal Water FuturesNational Science Foundation
KeywordsPrecambrianGeologyCrustGeothermal gradientPermeability (electromagnetism)GroundwaterGeochemistryPetrologyGeophysicsGeotechnical engineering

Abstract

fetched live from OpenAlex

The large volume of deep groundwater in the Precambrian crust has only recently been understood to be relatively hydrogeologically isolated from the rest of the hydrologic cycle. Currently, the paucity of permeability measurements in the Precambrian crust is a barrier to modeling fluid flow and solute transport in these low porosity and permeability deep environments. Estimates of permeability from prograde metamorphic rocks and geothermal systems have been applied to such groundwater systems, but, as data are few, it is unclear how appropriate this is for Precambrian crust on a global scale. To resolve this, we apply a new approach to constrain permeabilities for Precambrian crust to depths of 3.3 km based on fluid residence times estimated from noble gas analyses. The additional data reveals there is no statistically significant relationship at depths below 1 km, challenging the previous assumption of a global correlation between permeability and depth. Additionally, we show that estimated permeabilities at depths >1 km are at least an order of magnitude lower than previous estimates and possibly much lower. As a consequence, water and solute fluxes at these depths will be extremely limited, imposing important controls on elemental cycling and the distribution of subsurface microbial life.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.011
GPT teacher head0.218
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 source (direct Gemma or distilled Codex), 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
Published2022
Admission routes2
Has abstractyes

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