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Record W3195685806 · doi:10.36040/pawon.v5i2.3664

PENGEMBANGAN INFRASTRUKTUR BERBASIS RESILIENT CITY DI KOTA KENDARI SULAWESI TENGGARA

2021· article· id· W3195685806 on OpenAlex
Yudhi Dwi Hartono, Dian Puteri Nurbaity

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

VenuePawon Jurnal Arsitektur · 2021
Typearticle
Languageid
FieldSocial Sciences
TopicIndonesian Election Politics and Participation
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsGeographyHumanitiesArt

Abstract

fetched live from OpenAlex

Resilient city memiliki beberapa prinsip di antaranya prinsip ketahanan bencana, ketahanan pangan, ketahanan infrastruktur, ketahanan sosial, ketahanan sumber daya, serta integrasi alam. Melihat masalah yang ada di Kota Kendari, salah satu konsep yang paling efektif untuk diterapkan adalah konsep ketahanan infrastruktur. Sebagai mesin pertumbuhan, infrastruktur kota mempunyai risiko untuk terkena dampak bencana. Penelitian ini bertujuan untuk mengetahui kondisi eksisting infrastruktur yang ada di Kota Kendari serta bagaimana menerapkan prinsip-prinsip ketahanan kota (Resilient City) pada Infrastruktur di Kota Kendari khususnya di kawasan BWK V sebagai lokasi yang cukup rawan bencana banjir. Penelitian ini menggunakan metode deskriptif kualitatif dimana Cognitive Mapping digunakan sebagai teknik analisisnya. Hasil penelitian menunjukan bahwa kondisi infrastruktur di lokasi penelitian dari segi fisik belum memadai. Ketahanan infrastruktur yang berbasis pada resilient city dapat diterapkan mulai dari tahap perencanaan sampai pemeliharaan. Penelitian ini diharapkan dapat digunakan oleh pemerintah sebagai acuan dalam mengembangkan kota berketahanan terhadap bencana.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.344
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.300
Teacher spread0.271 · 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