Are floods getting worse in the Ganges, Brahmaputra and Meghna basins?
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
Abstract The Ganges, Brahmaputra and Meghna/Barak rivers are lifelines for millions of people in South Asia in Nepal, India, Bhutan and Bangladesh. They supply water for food and fibre production and for industrial and domestic purposes. They are also sources of disastrous floods that cause substantial damage to agriculture and infrastructure in these countries. There are claims that flood discharges, areal extent, and damage-costs are getting worse in the Ganges, Brahmaputra and Meghna/Barak basins. The validity of these claims was examined by applying four different statistical tests to the peak discharge time series and flooded areas. The results indicate that no conclusive changes have occurred over the last few decades. Reports of increased flood damage may be due to a combination of other factors, such as improved damage assessment techniques, and the expansion and intensification of settlement in flood-prone areas, but this was not tested in this paper and should be top priority for future research.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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