PASANGAN BRONJONG DAN BRONJONG KOMBINASI GEOBAG SEBAGAI PENANGANAN DARURAT UNTUK BANJIR DAN TANAH LONGSOR DI KAB. LAHAT
Bibliographic record
Abstract
Kabupaten Lahat merupakan salah satu kabupaten yang berada di Provinsi Sumatera Selatan. Kondisi alam berupa banjir merupakan salah satu bencana alam yang terjadi di Kabupaten Lahat. Hal ini menyebabkan Kabupaten Lahat sering terendam permukaan daratannya oleh genangan air. Debit air yang tinggi membuat sungai tidak mampu menampung seluruh aliran air sehingga membuat muka air melebihi elevasi tampungan air di sungai, dan menyebabkan banjir di Kab. Lahat ini. Penanggulangan bencana banjir dapat menggunakan pasangan bronjong di beberapa lokasi. Penggunaan pasangan bronjong dan batu dapat menjadi upaya cepat tanggap untuk pencegahan bencana banjir di kemudian hari. Pasangan batu bronjong dapat mencegah bencana banjir.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.105 | 0.022 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".