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Record W2791230305 · doi:10.1155/2018/6128401

Stability and Failure Mechanism Analyses of the Zhenggang Landslide in Southwestern China

2018· article· en· W2791230305 on OpenAlexaff
Shengnian Wang, Weiya Xu, Jinyuan Liu

Bibliographic record

VenueAdvances in Civil Engineering · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicLandslides and related hazards
Canadian institutionsToronto Metropolitan University
FundersGovernment of Jiangsu ProvinceNatural Science Foundation of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsLandslideGeologyLandslide classificationFailure mechanismPlateau (mathematics)Geotechnical engineeringChinaGeomorphologySeismologyArchaeologyGeographyEngineering

Abstract

fetched live from OpenAlex

The Zhenggang landslide is an ancient complex landslide located at southeastern Tibetan Plateau, China. Due to intensive rainfalls in 2008 and heavy snowfalls in 2009, the Zhenggang landslide exhibited a high probability of reactivation once again. In this study, geological structure, matter features, and macrodeformations of the Zhenggang landslide (including Zone I and Zone II) were investigated for uncovering its formation mechanism and evolution tendency first, and then the stability and failure mechanism analyses of the Zhenggang landslide were conducted in detail by a combined limit equilibrium and finite element analysis method. Results of geological investigations indicate that the Zhenggang landslide has undergone sliding several times and is in a metastable state now. The distribution of the activity of the landslide is a retrogressive landslide in Zone I but an advancing landslide in Zone II. Such conclusions are further proved by the numerical stability and failure analyses.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.230
Teacher spread0.223 · 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

Citations9
Published2018
Admission routes1
Has abstractyes

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