MétaCan
Menu
← Back to cohort
Record W4214924974 · doi:10.1139/cgj-2021-0230

Potassium chloride wells used as quick-clay landslide mitigation: installation procedures, cost–benefit analysis, and recommendations for design

2022· article· en· W4214924974 on OpenAlexvenueno aff
Tonje Eide Helle, Marianne Kvennås, Bob Hamel, Stein-Are Strand, G. Svanø, Bjørn Kristian Fiskvik Bache, Anders Samstad Gylland, Eigil Haugen, Christian Sætre, Toril Wiig, Atle Horn

Bibliographic record

VenueCanadian Geotechnical Journal · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsnot available
FundersStatens vegvesenNorges Teknisk-Naturvitenskapelige Universitet
KeywordsLandslideGeotechnical engineeringGeologyEnvironmental scienceMining engineering

Abstract

fetched live from OpenAlex

Retrogressive development of landslides in highly sensitive clays (quick clays) may extend several hundred metres upslope from an initial landslide, and liquified slide-debris may impact buildings or infrastructure in the run-out zone. By installing wells filled with potassium chloride (KCl) in quick clays, the salt migrates into the surrounding clay and increases its remolded shear strength, reducing its sensitivity. The salt-stabilized, nonquick clay volume may act as a barrier preventing backward retrogression, thereby contributing to reducing both the area susceptible for being involved in a quick-clay landslide, and the area of the run-out zone. Installation procedures and design guidelines for salt stabilization are examined herein. Installation procedures generating temporary, very small excess pore-water pressures were tested at National Geo-Test Site Tiller–Flotten. Although the benefit-to-cost ratios related to these procedures are small compared to conventional landslide mitigation measures, reducing the installation costs to less than 30 USD per m well and increasing the center distance between the wells may justify salt-stabilization as a landslide mitigation measure. This paper describes experience from testing safe installation procedures, evaluations of cost–benefit and environmental impact, and proposed design guidelines, introducing KCl as an alternative to conventional landslide mitigation-measures in slopes with highly sensitive quick-clay deposits.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.038
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.013
GPT teacher head0.239
Teacher spread0.225 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Geotechnical Journal→Same topicLandslides and related hazards→French-language works237,207→