Melting Away of Himalayan Glaciers and Resulting Water Shortages in India and Pakistan
Bibliographic record
Abstract
This paper deals with an important phenomenon taking place these days – melting of polar ice caps and glaciers on various mountains around the globe. This phenomenon has already affected the population in India and Pakistan due to the drying up of rivers. This is an indication for those living in South East Asia, and Far East that without the rivers to irrigate fields, there would be major food crisis. In addition, it would result in mass migration of people due to the shortage of water. This paper, at first, provides evidences of drying up processes of rivers Indus in Pakistan and Ganga in India—to show that the adverse effect of the global warming is already there in India and Pakistan, and this fact was completely missed out at the Copenhagen Conference in December 2009. Next, the paper shows that, without the glaciers on the Himalayas, vast areas in India and Pakistan would turn into deserts because in these areas the climate would change drastically due to lack of vegetation and influx of solar energy.
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How this classification was reachedexpand
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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".