Gγ-protein GS3 function downstream of OsmiR396/GS2 module to regulate grain size in rice
Bibliographic record
Abstract
Abstract Rice is one of the main crops in the world which provides food for more than one half world population. Grain size is tightly associated with grain weight, one of the three components determining yield in rice. Quite a few grain size determining quantitative trait loci (QTLs) have been identified, and several grain size-regulating signaling pathways been formed. Here, we showed that in the MIM396 plants, expression of GS3 gene was influenced. Through various biochemical assays, we proved that the miR396/GS2 module could directly regulate the Gg-protein GS3 to regulate grain size. Moreover, tight genetic association existed between miR396/GS2 and GS3. Moreover, other G-protein factors might also be connected with miR396/GS2 module, and thus factors from different pathways form a network to regulate grain size. Therefore, elucidation of these crosstalk would not only further our understanding of the molecular mechanism of grain size regulation, but also help guide modern crop breeding.
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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 | 0.000 |
| 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) | 0.002 | 0.001 |
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".