Bibliographic record
Abstract
Pembahasan musibah tidak lepas dari bencana, pembahasan musibah terdapat pada Alquran dan Hadis, musibah yang terjadi sering dikaitkan karena adanya sebab akibat dari ulah manusia itu sendiri, dari pernyataan tersebut masyarakat mengira bahwa bencana yang sering terjadi setiap tahunnya disebabkan oleh azab yang diturunkan oleh Allah SWT untuk menegur manusia. bencana atau musibah terjadi bukan hanya karena ulah tangan manusia, melainkan ada faktor alam dan takdir yang menyebabkan adanya bencana yang menimpa manusia di muka bumi. Tetapi meskipun begitu manusia harus tetap menjaga lingkungan agar dapat meminimalisir bencana yang sewaktu-waktu terjadi tanpa bisa diprediksi oleh tekhnologi. Adapun sikap yang harus manusia ambil dalam menghadapi bencana yaitu, seperti ridha dan ikhlas terhadap segala ketetapan yang telah Allah SWT turunkan kepada manusia, mencari pelajaran atau hikmah atas bencana yang menimpa manusia, baik karena faktor alam atau karena ulah tangan manusia. Selain itu, manusia harus memiliki sikap empati terhadap muslim lainnya dan mendoakan yang terbaik atas takdir yang diberikan Allah SWT kepada manusia, karena sesama muslim adalah saudara.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.108 | 0.040 |
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".