Control of cytoplasmic translation in plants
Bibliographic record
Abstract
Translational control provides cells with a mechanism to rapidly control gene expression in a reversible manner in response to environmental and developmental cues. It involves the dynamic, coordinated activity of numerous factors that direct the synthesis of proteins with precision in space and time. Translational control is primarily regulated at the level of initiation, and as such, mechanisms that regulate translation most often target the initiation machinery. Translation in plants is fundamentally similar to that of other eukaryotes. However, there are significant differences in translation factor isoforms and their associated proteins, and the types of regulation that can act upon these factors. Regulation of translation in plants can involve protein phosphorylation, variable associations of initiation factor isoforms, RNA sequence element interactions, and small RNAs. The assembly of large mRNA-ribonucleoprotein complexes, called processing bodies and stress granules, also influences the translatability of an mRNA. mRNA-cytoskeleton interactions, as well as subcellular and intercellular transport of mRNAs, also appear to regulate translation in plants. Often working together, these control mechanisms finely tune translational expression within the cell.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".