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Studi Perencanaan Bangunan Perkuatan Tebing Sebagai Upaya Pengendalian Longsor Sungai Kusan Kabupaten Tanah Bumbu Kalimantan Selatan

2023· article· id· W4398789423 on OpenAlex
Andhika Gymnastiar, Runi Asmaranto, Very Dermawan

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.

Bibliographic record

VenueJurnal Teknologi dan Rekayasa Sumber Daya Air · 2023
Typearticle
Languageid
FieldArts and Humanities
TopicArchitectural and Urban Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysics

Abstract

fetched live from OpenAlex

Sungai Kusan pada wilayah DAS Kusan banyak mengalami longsor pada tebing sungai akibat banjir pada bulan Januari-April 2021. Untuk itu perlu dilakukan perencanaan perkuatan tebing sungai agar dapat mencegah kerugian yang lebih besar. Pada studi ini, dilakukan analisis dengan beberapa metode untuk mengetahui perencanaan bangunan perkuatan tebing yang ideal berdasarkan kondisi profil aliran sungai dan kestabilan tebing eksisting. Dari hasil analisis, didapatkan penyebab longsor akibat gerusan sungai dan beberapa kondisi eksisting tebing tidak stabil. Berdasarkan kondisi tersebut, dilakukan pengendalian longsor dengan dinding penahan kantilever berdimensi 7x7 m. Pada pondasi kantilever di desain mini pile sepanjang 12 m, berjumlah 7 buah untuk meneruskan beban ke dalam lapisan tanah keras. Selain itu, ditambahkan desain blok beton dengan dimensi 0,7x0,7x0,7 m yang dilengkapi geotextile untuk mencegah gerusan pada tebing sungai dan pondasi kantilever. Berdasarkan kombinasi desain tersebut, maka pengendalian longsor pada tebing Sungai Kusan dapat diterima.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.189
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0060.002
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.002

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 head0.049
GPT teacher head0.265
Teacher spread0.217 · 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