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Record W4362687555 · doi:10.31293/teknikd.v8i1.6762

Analisis Tingkat Kerentanan Terhadap Potensi Bahaya Kebakaran di Permukiman Padat Penduduk di Kelurahan Pelita Kecamatan Samarinda Ilir Kota Samarinda

2020· article· id· W4362687555 on OpenAlexaff
Findia Findia

Bibliographic record

VenueKurva S Jurnal Keilmuan dan Aplikasi Teknik Sipil · 2020
Typearticle
Languageid
FieldHealth Professions
TopicOccupational Health and Safety Management
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsPhysicsForestryGeography

Abstract

fetched live from OpenAlex

Penelitian ini mengkaji tentang nilai tingkat kerentanan terhadap potensi bahaya kebakaran di kelurahan Pelita. Teknik analisis data yang digunakan dalam penelitian ini adalah metode skoring untuk mengidentifikasi nilai tingkat kerentanan terhadap potensi kebakaran berdasarkan variabel potensi kebakaran yang terdiri atas kepadatan bangunan rumah mukim, pola bangunan rumah mukim, jenis atap bangunan rumah mukim, lokasi sumber air, lebar jalan masuk, kepadatan lalu lintas kelistrikan, keterjangkaun hidran, ketersediaan tendon air, usia bangunan dan dinding bangunan. Berdasarkan hasil pengamatan GPS Area Measurement dan survey, wilayah yang menjadi sampel penelitian yaitu di jalan Lambung Mangkurat Gg Masjid akan dibagi menjadi 4 blok permukiman (blok I, II, III, IV) dengan menggunakan metode grid. Dari hasil analisis diketahui keempat blok masuk dalam kategori tinggi dengan skor masing-masing 26, 26, 29 dan 27.

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 score0.074
Threshold uncertainty score0.147

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
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 head0.063
GPT teacher head0.338
Teacher spread0.275 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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