The Effect and Mechanism Analysis of High Temperature on Rice Pollen Development and Pollination
Bibliographic record
Abstract
This study aims to delve into the impact of high temperature on rice pollen development and pollination processes, along with its underlying mechanisms. With the ongoing global temperature rise, high-temperature stress poses a severe challenge to rice production. We scrutinize the fundamental processes of rice pollen development, with a particular focus on the temperature sensitivity during critical developmental stages. The study extensively analyzes the involvement of hormone signaling pathways in rice under high-temperature conditions, highlighting the variations and physiological significance of hormones such as ABA, GA, and ethylene. At the molecular level, we delve into the regulation of rice protein synthesis and metabolism under high temperature, revealing alterations in protein synthesis rates and composition. Moreover, we propose recommendations for future research and agricultural practices, emphasizing the cultivation of high-temperature-adaptive rice varieties through genetic improvement and agricultural management strategies. This research provides a theoretical foundation for a profound understanding of the impact of high temperature on rice reproductive processes, contributing to the achievement of sustainable agriculture and global food security.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".