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Record W3110460707 · doi:10.1051/e3sconf/202019501015

Stability Analysis of Unsupported Vertical Cuts in the Vadose Zone using 2D and 3D Numerical Methods

2020· article· en· W3110460707 on OpenAlexaff
Gregory Brennan, Won Taek Oh, Othman Nasir

Bibliographic record

VenueE3S Web of Conferences · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsVadose zoneStability (learning theory)GeologyGeotechnical engineeringNumerical analysisLimit (mathematics)Slope stability analysisSlope stabilityMathematicsComputer scienceGroundwaterMathematical analysis

Abstract

fetched live from OpenAlex

Evidence supporting the implementation of three-dimensional (3D) slope stability analysis in geotechnical engineering practice has been mounting since the nineteen-seventies. Current levels of computational power and its accessibility has allowed researchers to investigate the significance of the 3D numerical analysis output compared to conventional 2D limit equilibrium approach. This study compares results of stability analyses of unsupported vertical cuts in the vadose zone using both 2D (GeoStudio 2019 R2) and 3D (FLAC3D) software. Numerical analyses are carried out for various dimensions of unsupported vertical cuts excavated in an unsaturated glacial till. The findings from two different methods (i.e. 2D and 3D) and the limitations of 2D stability analysis are discussed.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.453
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

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

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 head0.048
GPT teacher head0.315
Teacher spread0.267 · 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.

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

Citations1
Published2020
Admission routes1
Has abstractyes

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