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Record W4388670760 · doi:10.24929/ft.v11i2.2319

EVALUASI SISTEM PENGAMAN PANTAI DI BALI SELATAN UNTUK MENGATASI TANTANGAN PERUBAHAN IKLIM

2023· article· id· W4388670760 on OpenAlexaff
Kadek Windy Candrayana, I Nengah Sinarta, I Gusti Agung Putu Eryani

Bibliographic record

VenueJurnal Ilmiah MITSU (Media Informasi Teknik Sipil Universitas Wiraraja) · 2023
Typearticle
Languageid
FieldEngineering
TopicGeotechnical and construction materials studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysicsForestryGeography

Abstract

fetched live from OpenAlex

Perubahan iklim ini berdampak pada pesisir Indonesia yang menyebabkan erosi dan banjir rob. Kerusakan pesisir ini berdampak signifikan pada area vital yang berupa kawasan wisata seperti pada pantai Selatan Bali. Laju erosi pada pantai Bali yang saat ini mencapai 2 m/tahun dan sangat berdampak pada keberadaan objek wisata pantai di Bali. Struktur pengaman pantai dibangun dari tahun 1990an hingga saat ini didominasi seawall dan revetment. Struktur eksisting mengalami permasalahan yaitu terjadi banjir rob dan limpasan pada mercu bangunan. Metode yang digunakan adalah dengan menganalisis perubahan tinggi muka air laut dari waktu ke waktu (time series) serta simulasi numeris dengan CMS-Wave untuk memperoleh tinggi gelombang pada struktur. Muka air ekstrem (Extreme Coastal Water Level) dihitung dari rayapan akibat tinggi gelombang, kenaikan muka air laut, pasang surut dan badai. Hasil penelitian ini menunjukkan kenaikan muka air pada tahun 2022 menyebabkan 53.80% bangunan mengalami overtopping. Pada 20 tahun mendatang (2042) persentase bangunan yang mengalami overtopping meningkat menjadi 67.08%.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.469
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.003

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 head0.018
GPT teacher head0.211
Teacher spread0.194 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2023
Admission routes1
Has abstractyes

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