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Record W2983005376 · doi:10.25105/psia.v1i1.5983

ANALISIS PENURUNAN TANAH LUNAK AKIBAT PENIMBUNAN BERTAHAP

2019· article· id· W2983005376 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.

Bibliographic record

VenueProsiding Seminar Intelektual Muda · 2019
Typearticle
Languageid
FieldEngineering
TopicGeotechnical and construction materials studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysicsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Pada suatu konstruksi diperlukan tanah pondasi yang cukup kuat untuk menahan beban yang nantinya diberikan di atasnya. Pada tanah lunak, konstruksi sangat sulit dilakukan karena tanah lunak karena memiliki daya dukung yang rendah dan penurunan yang cukup besar juga waktu penurunan maksimum yang sangat lama keran permeabilitasnya yang rendah. Maka dari itu, diperlukan sebuah metode untuk dilakukan perbaikan pada tanah jenis ini. Metode perbaikan tanah yang dipakai ialah penimbunan tanah secara bertahap, sehingga layak dan memenuhi persyaratan sebagai lapisan pondasi. Penimbunan bertahap dapat dilakukan dengan memberikan pembebanan berupa tanah yang dirasa cukup baik untuk dijadikan tanah timbunan, untuk memperkuat tanah yang akan ditimbun. Berdasarkan hasil analisis yang dilakukan, dihasilkan nilai kuat geser tanah ( ) yang semakin tinggi disetiap tahapan penimbunan.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.004

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 head0.204
Teacher spread0.197 · 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