An Assessment of the Adaptability to Climate Change of Commercially Available Maize Varieties in Zimbabwe
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 study was undertaken to assess the adaptability to climate change of commercially available maize varieties in Zimbabwe using 2010, 2020, 2050 and 2080 climate change scenarios. The FAO’s Ecocrop Model was used to assess the suitability of early, short, medium and long season maize varieties grown under rainfed conditions in different agro-ecological regions (1 to 5) whose agricultural potential decreases progressively due to the amount of rainfall received. Regions 1 and 2 conditions are projected to decrease in size by 14%, region 3 by 26%, while regions 4 and 5 are projected to increase by 40%. The area suitable for growing early low yielding maize varieties will remain at nearly 100% in regions 1 and 2. The area suitable for growing medium maturing varieties will decline to below 20% in regions 4 and 5. Overall, only 2% of Zimbabwe s’ land area, mainly in region 1, will be suitable for growing high yielding late maturing maize varieties. The paper concludes that the currently available maize germplasm in the country is not suitable for the projected climate change conditions.
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 | 0.002 | 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) | 0.001 | 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