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Record W3208050096 · doi:10.33005/envirotek.v13i2.121

ANALISIS SPASIAL TITIK DAN JALUR EVAKUASI DALAM MITIGASI PENGURANGAN RISIKO BENCANA BANJIR DI KECAMATAN MANDONGA KOTA KENDARI

2021· article· id· W3208050096 on OpenAlexaff
Hasddin Hasddin, Erny Tamburaka

Bibliographic record

VenueJURNAL ENVIROTEK · 2021
Typearticle
Languageid
FieldComputer Science
TopicMultimedia Learning Systems
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysics

Abstract

fetched live from OpenAlex

Penelitian ini menganalisis sebaran wilayah banjir dan penentuan tempat dan jalur evakuasi di Kecamatan Mandonga, Kota Kendari. Penelitian menggunakan desain kuantitatif dan survei. Data dianalisis secara spasial dengan aplikasi ArcView 3.2. Hasil penelitian menunjukkan bahwa banjir yang terjadi di Kecamatan Mandonga, Kota Kendari selama tahun 2015-2018 seluas 416,23 ha atau sekitar 37,45 % dari total luas wilayah Kecamatan Mandonga (1.111,47 ha), tersebar diseluruh wilayah (di enam kelurahan). Ada enam (6) titik yang layak sebagai tempat evakuasi utama pengungsian banjir di Kecamatan Mandonga, 1 titik di Kelurahan Labibia, 2 titik di Kelurahan Wawombalata, dan 3 titik di Kelurahan Mandonga. Ada 11 titik jalur yakni; Jl. Imam Bonjol; Jl. Subsidi; Jl. Sawerigading (Anggilowu); Jl. Sawerigading (Mandonga); Jl. Taridala; Jl. Lasandara; Jl. Made Sabara; Jl. Pajak; Jl. Welado; Jl. Supu Yusuf; dan Jl. Sidendreng.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.002

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 head0.013
GPT teacher head0.238
Teacher spread0.225 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2021
Admission routes1
Has abstractyes

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Same venueJURNAL ENVIROTEKSame topicMultimedia Learning SystemsFrench-language works237,207