Calculating the cost of irrigation induced soil salinization in the tungabhadra project
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 Irrigation projects in developing countries have a history of poor performance. Inefficiencies result as water applications deviate from plans and induce greater than projected rates of soil degradation through water logging and salt accumulation. Over time, the collective impact of these forces will converge to an equilibrium with a level of output that may be far below the system's potential. The Tungabhadra Project in south west India is experiencing all of these problems. Integrating geographic, hydrologic, biologic and economic features, the lost production value is estimated for a range of equilibria to which this system may converge. For the lower left bank main canal of the Tungabhadra project, the total economic cost of soil degradation are approximately 14.5% of the system's productive potential while sub‐optimal distribution losses may approach 37.1%
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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 it