Functional genomics of seed dormancy in wheat: advances and prospects
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
Seed dormancy is a mechanism underlying the inability of viable seeds to germinate under optimal environmental conditions. To achieve rapid and uniform germination, wheat and other cereal crops have been selected against dormancy. As a result, most of the modern commercial cultivars have low level of seed dormancy and are susceptible to preharvest sprouting when wet and moist conditions occur prior to harvest. As it causes substantial loss in grain yield and quality, preharvest sprouting is an ever-present major constraint to the production of wheat. The significance of the problem emphasizes the need to incorporate an intermediate level of dormancy into elite wheat cultivars, and this requires detailed dissection of the mechanisms underlying the regulation of seed dormancy and preharvest sprouting. Seed dormancy research in wheat often involves after-ripening, a period of dry storage during which seeds lose dormancy, or comparative analysis of seeds derived from dormant and non-dormant cultivars. The increasing development in wheat genomic resources along with the application of transcriptomics, proteomics, and metabolomics approaches in studying wheat seed dormancy have extended our knowledge of the mechanisms acting at transcriptional and post-transcriptional levels. Recent progresses indicate that some of the molecular mechanisms are associated with hormonal pathways, epigenetic regulations, targeted oxidative modifications of seed mRNAs and proteins, redox regulation of seed protein thiols, and modulation of translational activities. Given that preharvest sprouting is closely associated with seed dormancy, these findings will significantly contribute to the designing of efficient strategies for breeding preharvest sprouting tolerant wheat.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 | 0.000 |
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