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Record W7117382194 · doi:10.36873/jht.v20i2.22996

Pendekatan Citra Satelit Dalam Analisis Perubahan Vegetasi Di Daerah Pesisir Baurung

2025· article· W7117382194 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

VenueHUTAN TROPIKA · 2025
Typearticle
Language
FieldEngineering
TopicWetland Management and Conservation
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsHydrology (agriculture)Vegetation (pathology)Population

Abstract

fetched live from OpenAlex

Wilayah pesisir Baurung di Kabupaten Majene mengalami perubahan tutupan vegetasi yang signifikan akibat urbanisasi dan pembangunan pesat dalam dekade terakhir, yang menyebabkan penurunan ruang terbuka hijau dan kualitas ekosistem pesisir. Penelitian ini bertujuan untuk menganalisis perubahan vegetasi di daerah pesisir Baurung menggunakan pendekatan citra satelit resolusi tinggi yang dikombinasikan dengan metode interpolasi spasial Kriging. Dengan teknik ini, diperoleh peta prediksi vegetasi yang detail dan akurat, memungkinkan identifikasi area yang mengalami degradasi maupun area dengan tutupan vegetasi tinggi yang perlu dipertahankan. Hasil penelitian menunjukkan adanya penyusutan signifikan vegetasi alami dengan peningkatan area terbangun di sepanjang pesisir, berpotensi memperburuk risiko erosi, banjir rob, dan degradasi ekologis. Pendekatan ini memberikan alat penting bagi pengelolaan ruang terbuka hijau yang adaptif dan berkelanjutan serta sebagai dasar kebijakan mitigasi perubahan iklim di wilayah pesisir Baurung.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.341
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.008
GPT teacher head0.219
Teacher spread0.211 · 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