Envisioning a sustainable agricultural water future across spatial scales
Bibliographic record
Abstract
Abstract Sustainable agricultural water systems are critical to ensure prosperous agricultural production, secure water resources, and support healthy ecosystems that sustain livelihoods and well-being. Many growing regions are using water unsustainably, leading to groundwater and streamflow depletion and polluted water bodies. Often, this is driven by global consumer demands, with environmental and social impacts occurring in regions far from where the crop is ultimately consumed. This letter defines sustainable agricultural water limits, both for quantity and quality, tying them to the impacts of agricultural water use, such as impacts on ecosystems, economies, human health, and other farmers. Imposing these limits will have a range of both positive and negative impacts on agricultural production, food prices, ecosystems, and health. Pathways forward exist and are proposed based on existing studies, showing the gains that can be made from the farm to global scale to ensure sustainable water systems while sustaining agricultural production.
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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 | 0.001 |
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 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".