IDENTIFIKASI LOKASI RAWAN BENCANA BANJIR LAHAR DI DAERAH ALIRAN SUNGAI PABELAN, MAGELANG, JAWA TENGAH
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.
Bibliographic record
Abstract
Daerah Aliran Sungai (DAS) Pabelan merupakan salah satu sungai yang paling rawan mengalami banjir lahar pascaerupsi Gunungapi Merapi tahun 2010. Kejadian banjir lahar merusak di DAS ini terjadi sebanyak 17 kali sejak erupsi tahun 2010, terbanyak kedua setelah DAS Putih. Penelitian ini bertujuan mengidentifikasi wilayah rawan banjir lahar berdasarkan pada sensus dampak banjir lahar yang terjadi pasca erupsi Merapi Tahun 2010. Sensus dilakukan dengan melakukan identifikasi lokasi yang mengalami kerusakan dengan citra penginderaan jauh resolusi tinggi di lokasi kajian. Selain itu, identifikasi dilakukan dengan wawancara dengan seluruh pemerintah tingkat dusun dan desa yang wilayahnya dilalui aliran Sungai utama Pabelan. Hasil analisis menunjukkan bahwa lokasi rawan bencana banjir lahar terdiri dari 27 titik yang tersebarmulai dari hulu sampai dengan hilir DAS Pabelan.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.011 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it