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Record W4392976047 · doi:10.1139/cgj-2023-0463

Modelling the impact of deep fractures on groundwater flow and slope stability in post-glacial marine clays (Quebec, Canada)

2024· article· en· W4392976047 on OpenAlexaffvenueabout
Julián Andrés Ospina Llano, Nathan Young, Jean‐Michel Lemieux, John Molson, Ariane Locat, Pascal Locat

Bibliographic record

VenueCanadian Geotechnical Journal · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsMinistère des TransportsCenter for Northern StudiesUniversité LavalHôpital Saint-François d'Assise
Fundersnot available
KeywordsGroundwater flowGeologyGlacial periodGeotechnical engineeringSlope stabilityGroundwaterDebris flowGeomorphologyOceanographyAquiferDebris

Abstract

fetched live from OpenAlex

It is usually assumed that post-glacial marine clay deposits, such as those found in Quebec, are generally intact below a shallow fractured crust (3–5 m depth). However, recent work has shown the presence of hydraulically-active fractures to depths of down to 16 m. In light of this finding, the potential impacts of these fractures on groundwater flow dynamics and slope stability are explored by comparing field data with the results of transient and steady-state groundwater models with and without fractures. Two slope geometries that exhibit contrasting groundwater flow directions and different fracture scenarios were considered. The results of the hydrogeological modelling were then imported into a slope stability model to determine how the hydraulic effects of these fractures impact slope stability. Results show that fractures increase hydraulic head when they act as preferential pathways for infiltration, but can also reduce hydraulic head by acting as pathways for water to more quickly exit the formation within the slope face. Therefore, from a hydrogeological perspective, fractures could improve or reduce slope stability depending on the groundwater flow system. As this study only addressed the hydrogeological impact of the fractures, future work should focus on the coupled hydromechanical impacts of these features.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.211
Teacher spread0.204 · 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 designSimulation or modeling
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

Citations2
Published2024
Admission routes3
Has abstractyes

Explore more

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