Heat stress in wheat: a global challenge to feed billions in the current era of the changing climate
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
Crop failure is largely caused by various climate hazards, and among them, heat stress is the primary factor hindering crop production. The significant global loss of crop yield is primarily due to heat-related damage during the reproductive phase. Terminal heat stress has been well documented in wheat, causing morphophysiological alterations, biochemical disruptions, and reduction of genetic potential. The formation of shoots and roots, the effect on the double ridge stage, and early biomass in the vegetative stage are also impacted by heat stress. The final negative outcomes of heat stress include reduced grain number and weight, slower grain filling rate, reduced grain quality, and shorter grain filling duration. Plants have developed mechanisms to adapt to heat stress through modifications in their morphological or growth responses, physiological and biochemical pathways, and changes in enzyme reactions. Numerous heat tolerance genes have been identified in wheat, but the more extensive study is needed to increase heat tolerance in crops to satisfy the food demands of the world’s growing population. The global food policy needs to prioritize and promote additional joint research and the development of heat-tolerant wheat breeding to ensure the world’s food security.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.005 |
| 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