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Record W4412137911 · doi:10.37253/jcep.v5i2.10007

Stability Modeling of Groyne-Type Structure with Embankment in Pelangai River, Pesisir Selatan Regency, West Sumatra

2024· article· en· W4412137911 on OpenAlexaff
Riko Zulhendra, Maulana Arif, Dicky Febri Hadi

Bibliographic record

VenueJournal of Civil Engineering and Planning · 2024
Typearticle
Languageen
FieldEngineering
TopicGeotechnical and construction materials studies
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsLeveeGeologyGeotechnical engineeringStructure typeHydrology (agriculture)Chemistry

Abstract

fetched live from OpenAlex

Erosion is one of the exogenic processes that commonly occur around river dynamics. Intensive erosion occurs at the riverbank area, which has the potential to cause the slope on that side to collapse. Therefore, a groyne-type structure is required to prevent this from happening. A groyne-type structure is planned to reduce the impact of erosion in the Pelangai River with embankment. This research aims to determine the stability of the groyne with embankment design using Plaxis 2D software. Plaxis 2D modeling uses soil input parameters based on CPT, SPT, and groyne structure with approximation parameters. The modeling results show that with the addition of groyne, embankment and traffic load, the safety number drops from 1.906 to 1.241. This figure does not meet the safe number limit according to SNI Geotechnical 8460 of 2017, which requires a minimum safe number of 1.25. In addition, the addition of groyne, embankment, and traffic load resulted in soil settlement of up to 6.3 cm, which is still considered safe.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.010
GPT teacher head0.193
Teacher spread0.184 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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