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Record W4392257291 · doi:10.54199/pjse.v3i1.166

Identifikasi Perumahan di Lokasi Rawan Bencana Kabupaten Jepara

2023· article· id· W4392257291 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

VenuePerwira Journal of Science & Engineering · 2023
Typearticle
Languageid
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Fiscal Policies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsAgricultural scienceBiology

Abstract

fetched live from OpenAlex

Bencana alam merupakan peristiwa alam yang menimbulkan resiko atau bahaya bagi kehidupan manusia. Akibat yang ditimbulkan dari bencana tersebut adalah kerugian jiwa maupun harta benda, manusia, dan kerusakan terhadap lingkungan. Kabupaten Jepara memiliki kawasan rawan bencana alam yang diantaranya meliputi kawasan rawan abrasi, banjir, gerakan tanah/ longsor, dan puting beliung dimana pada umumnya terjadi di kawasan permukiman penduduk sehingga menyebabkan kerusakan rumah beserta lingkungannya. Kerusakan tersebut perlu mendapatkan perhatian karena akan berdampak terhadap menurunnya kualitas hidup masyarakat apabila tidak ada antsipasi/penanganan yang tepat dan terencana. Tujuan penelitian ini adalah mengidentifikasi sebaran perumahan di lokasi rawan bencana di wilayah Kabupaten Jepara. Analisis deskriptif digunakan dalam penelitian untuk melihat permasalahan dan kondisi secara fisik lokasi yang rawan terhadap bencana alam yang ada. Hasil lain yang diharapkan melalui penelitian ini adalah dapat mengetahui karakteristik dari perumahan di lokasi rawan bencana sehingga dapat menjadi pertimbangan dalam memberikan arahan dan rekomendasi kebijakan untuk penanganan perumahan di lokasi yang rawan bencana di Kabupaten Jepara.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.211
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.024
GPT teacher head0.223
Teacher spread0.199 · 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