Combinatorial Networks Regulating Seed Development and Seed Filling
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
Embryogenesis 190 shapes and sizes, a common element in plant seeds is the storage reserves that generally consist of starch, storage lipid triacylglycerols (TAGs) and specialized seed storage proteins (SSPs). Given the importance of seeds, such as those of legumes or cereals, in human and animal diets, much research has been devoted to improving qualitative and quantitative traits associated with seed components such as palatability and nutritional quality. As such, understanding the metabolism and development during seed filling has been a major focus of plant research. The recent development of a range of chemical, physiological, molecular genetics and post-genomics approaches has allowed rapid progress toward understanding the processes of early seed development, maturation, dormancy, after-ripening and germination, but has also provided opportunities to control and modify both the quality and quantity of seed products In recent years, much effort has been devoted to elucidating the intricate regulatory networks that control seed development and maturation, where hormone and sugar signaling together with a set of developmentally regulated transcription factors and chromatin remodeling proteins are involved. Here, we summarize the most recent advances in our understudying of this complex regulatory network and its role in the control of seed development and seed filling.
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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) | 0.000 | 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 | 0.001 | 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