The Groundwater Recovery Paradox in South India
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 Reported groundwater recovery in South India has been attributed to both increasing rainfall and political interventions. Findings of increasing groundwater levels, however, are at odds with reports of well failure and decreases in the land area irrigated from shallow wells. We argue that recently reported results are skewed by the problem of survivor bias, with dry or defunct wells being systematically excluded from trend analyses due to missing data. We hypothesize that these dry wells carry critical information about groundwater stress that is missed when data are filtered. Indeed, we find strong correlations between missing well data and metrics related to climate stress and groundwater development, indicative of a systemic bias. Using two alternative metrics, which take into account information from dry and defunct wells, our results demonstrate increasing groundwater stress in South India. Our refined approach for identifying groundwater depletion hot spots is critical for policy interventions and resource allocation.
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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 | 0.001 |
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