Millets for Food Security in the Context of Climate Change: A Review
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
A growing population means an ever-increasing demand for food. This global concern has led to antagonism over resources such as water and soil. Climate change can directly influence the quality and availability of these resources, thereby adversely affecting our food systems and crop productivity, especially of major cereals such as rice, wheat and maize. In this review, we have looked at the availability of resources such as water and soil based on several modeling scenarios in different regions of the world. Most of these models predict that there will be a reduction in production rates of various cereal crops. Furthermore, all the major cereal crops are known to have a higher contribution to global warming than alternative crops such as millets which should be considered in mitigating global food insecurity. In this study, we have used the data to predict which regions of the world are most adversely affected by climate change and how the cultivation of millets and other crops could aid in the reduction of stress on environmental resources.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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