Interdisciplinary discussions of hydrology and river linking take place in India
Bibliographic record
Abstract
Considerable investment has been made in the development, construction, and management of water resources projects in the past 150 years. Many of these projects have caused deleterious environmental consequences, such as erosion and sedimentation of reservoirs, water logging, and alkalinization and salinization of irrigated lands. With the rising demand worldwide for quality water, the increasing call for preservation of environmental quality and sustenance of biodiversity, and the simultaneous and growing acceptance that the water use and management strategies of the past have often been unsustainable, there is an urgent need for wide‐ranging discussions of past water resources policies and practices. Scientists, engineers, planners, managers, administrators, and policy makers recently met in Bhopal, India, to discuss problems and exchange ideas pertaining to water, water use, and the environment in arid, semi‐arid, subhumid, humid, and tropical regions. More than 400 participants representing 30 countries, including Australia, Canada, India, Germany, France, Italy the United States, and the United Kingdom, among others attended Water and Environment (WE)‐2003.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".