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Record W2409882520 · doi:10.1080/19475705.2015.1081633

A study on the fractal characteristics of displacement time-series during the evolution of landslides

2015· article· en· W2409882520 on OpenAlexaff
Weiya Xu, Qingxiang Meng, R. B. Wang, J. C. Zhang

Bibliographic record

VenueGeomatics Natural Hazards and Risk · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsUniversity of Waterloo
FundersNational Key Research and Development Program of ChinaKey Technologies Research and Development ProgramMajor State Basic Research Development Program of China
KeywordsLandslideFractal dimensionFractalSeries (stratigraphy)Displacement (psychology)GeologyStability (learning theory)Geotechnical engineeringMathematicsStatistical physicsMathematical analysisPhysicsComputer science

Abstract

fetched live from OpenAlex

Landslides are one of the major natural disasters that are frequently occurring in southwestern China.The main objective of this study is to investigate the relationship between failure of landslide and fractal dimension using displacement time-series.Taking two slopes in southwestern China as examples, we estimate the fractal parameters of displacement timeseries and analyze the relationship between fractal dimension and the stability of the slope during the evolution of landslides.The result shows that the fractal dimension increases when a landslide undergoes a transition from stability to failure, but decreases during the evolution from active to stable.Fractal dimension has a critical value of 1.10 in the transition between active and stable, which indicates that fractal dimension is an important nonlinear parameter in the evaluation of the stability of landslides, although more studies and in situ data are required for validation.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.191

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.005
GPT teacher head0.209
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 teacher head, 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

Citations8
Published2015
Admission routes1
Has abstractyes

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