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Record W4404321625 · doi:10.3390/geotechnics4040059

Parametric Study of Rainfall-Induced Instability in Fine-Grained Sandy Soil

2024· article· en· W4404321625 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueGeotechnics · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsInstabilityEnvironmental scienceParametric statisticsGeologyGeotechnical engineeringSoil scienceMathematicsPhysics

Abstract

fetched live from OpenAlex

This study investigates the stability of fine-grained sandy soil slopes under varying rainfall intensities, durations, and geotechnical properties using a parametric analysis within GeoStudio. A total of 4416 unique parameter combinations were analyzed, incorporating variations in unit weight, cohesion, friction angle, slope inclination, slope height, rainfall intensity, and duration. Results reveal that rainfall intensity is the most influential variable on the factor of safety (FS), with higher intensities (e.g., 360 mm/h) on steeper slopes (e.g., 45°) leading to critical FS values below 1, indicating an imminent risk of failure. Under moderate conditions (e.g., 9 mm/h rainfall on slopes of 26.6°), the FS remains above 2. This dataset provides a valuable foundation for training machine learning models to predict slope stability under diverse environmental conditions, contributing to the development of early warning systems for rainfall-induced landslides.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.445
Threshold uncertainty score0.408

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.013
GPT teacher head0.248
Teacher spread0.234 · 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